Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

Structure and Ligand Based Drug Design Strategies in the Development of Novel 5-LOX Inhibitors

PubMed Central

Aparoy, Polamarasetty; Kumar Reddy, Kakularam; Reddanna, Pallu

2012-01-01

Lipoxygenases (LOXs) are non-heme iron containing dioxygenases involved in the oxygenation of polyunsaturated fatty acids (PUFAs) such as arachidonic acid (AA). Depending on the position of insertion of oxygen, LOXs are classified into 5-, 8-, 9-, 12- and 15-LOX. Among these, 5-LOX is the most predominant isoform associated with the formation of 5-hydroperoxyeicosatetraenoic acid (5-HpETE), the precursor of non-peptido (LTB4) and peptido (LTC4, LTD4, and LTE4) leukotrienes. LTs are involved in inflammatory and allergic diseases like asthma, ulcerative colitis, rhinitis and also in cancer. Consequently 5-LOX has become target for the development of therapeutic molecules for treatment of various inflammatory disorders. Zileuton is one such inhibitor of 5-LOX approved for the treatment of asthma. In the recent times, computer aided drug design (CADD) strategies have been applied successfully in drug development processes. A comprehensive review on structure based drug design strategies in the development of novel 5-LOX inhibitors is presented in this article. Since the crystal structure of 5-LOX has been recently solved, efforts to develop 5-LOX inhibitors have mostly relied on ligand based rational approaches. The present review provides a comprehensive survey on these strategies in the development of 5-LOX inhibitors. PMID:22680930

Quantitative structure-activity relationship: promising advances in drug discovery platforms.

PubMed

Wang, Tao; Wu, Mian-Bin; Lin, Jian-Ping; Yang, Li-Rong

2015-12-01

Quantitative structure-activity relationship (QSAR) modeling is one of the most popular computer-aided tools employed in medicinal chemistry for drug discovery and lead optimization. It is especially powerful in the absence of 3D structures of specific drug targets. QSAR methods have been shown to draw public attention since they were first introduced. In this review, the authors provide a brief discussion of the basic principles of QSAR, model development and model validation. They also highlight the current applications of QSAR in different fields, particularly in virtual screening, rational drug design and multi-target QSAR. Finally, in view of recent controversies, the authors detail the challenges faced by QSAR modeling and the relevant solutions. The aim of this review is to show how QSAR modeling can be applied in novel drug discovery, design and lead optimization. QSAR should intentionally be used as a powerful tool for fragment-based drug design platforms in the field of drug discovery and design. Although there have been an increasing number of experimentally determined protein structures in recent years, a great number of protein structures cannot be easily obtained (i.e., membrane transport proteins and G-protein coupled receptors). Fragment-based drug discovery, such as QSAR, could be applied further and have a significant role in dealing with these problems. Moreover, along with the development of computer software and hardware, it is believed that QSAR will be increasingly important.

Advances in Mycobacterium tuberculosis therapeutics discovery utlizing structural biology

PubMed Central

Chim, Nicholas; Owens, Cedric P.; Contreras, Heidi; Goulding, Celia W.

2013-01-01

In 2012, tuberculosis (TB) remains a global health threat and is exacerbated both by the emergence of drug resistant Mycobacterium tuberculosis strains and its synergy with HIV infection. The waning effectiveness of current treatment regimens necessitates the development of new or repurposed anti-TB therapeutics for improved combination therapies against the disease. Exploiting atomic resolution structural information of proteins in complex with their substrates and/or inhibitors can facilitate structure-based rational drug design. Since our last review in 2009, there has been a wealth of new M. tuberculosis protein structural information. Once again, we have compiled the most promising structures with regards to potential anti-TB drug development and present them in this updated review. PMID:23167715

Structure-based drug design enables conversion of a DFG-in binding CSF-1R kinase inhibitor to a DFG-out binding mode

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meyers, Marvin J.; Pelc, Matthew; Kamtekar, Satwik

2010-08-11

The work described herein demonstrates the utility of structure-based drug design (SBDD) in shifting the binding mode of an HTS hit from a DFG-in to a DFG-out binding mode resulting in a class of novel potent CSF-1R kinase inhibitors suitable for lead development.

Drug Distribution. Part 1. Models to Predict Membrane Partitioning.

PubMed

Nagar, Swati; Korzekwa, Ken

2017-03-01

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

Supramolecular Drug Delivery Systems Based on Water-Soluble Pillar[n]arenes.

PubMed

Wu, Xuan; Gao, Lei; Hu, Xiao-Yu; Wang, Leyong

2016-06-01

Supramolecular drug delivery systems (SDDSs), including various kinds of nanostructures that are assembled by reversible noncovalent interactions, have attracted considerable attention as ideal drug carriers owing to their fascinating ability to undergo dynamic switching of structure, morphology, and function in response to various external stimuli, which provides a flexible and robust platform for designing and developing functional and smart supramolecular nano-drug carriers. Pillar[n]arenes represent a new generation of macrocyclic hosts, which have unique structures and excellent properties in host-guest chemistry. This account describes recent progress in our group to develop pillararene-based stimuli-responsive supramolecular nanostructures constructed by reversible host-guest interactions for controllable anticancer drug delivery. The potential applications of these supramolecular drug carriers in cancer treatment and the fundamental questions facing SDDSs are also discussed. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Antiviral agents: structural basis of action and rational design.

PubMed

Menéndez-Arias, Luis; Gago, Federico

2013-01-01

During the last 30 years, significant progress has been made in the development of novel antiviral drugs, mainly crystallizing in the establishment of potent antiretroviral therapies and the approval of drugs inhibiting hepatitis C virus replication. Although major targets of antiviral intervention involve intracellular processes required for the synthesis of viral proteins and nucleic acids, a number of inhibitors blocking virus assembly, budding, maturation, entry or uncoating act on virions or viral capsids. In this review, we focus on the drug discovery process while presenting the currently used methodologies to identify novel antiviral drugs by using a computer-based approach. We provide examples illustrating structure-based antiviral drug development, specifically neuraminidase inhibitors against influenza virus (e.g. oseltamivir and zanamivir) and human immunodeficiency virus type 1 protease inhibitors (i.e. the development of darunavir from early peptidomimetic compounds such as saquinavir). A number of drugs in preclinical development acting against picornaviruses, hepatitis B virus and human immunodeficiency virus and their mechanism of action are presented to show how viral capsids can be exploited as targets of antiviral therapy.

Modeling Liver-Related Adverse Effects of Drugs Using kNN QSAR Method

PubMed Central

Rodgers, Amie D.; Zhu, Hao; Fourches, Dennis; Rusyn, Ivan; Tropsha, Alexander

2010-01-01

Adverse effects of drugs (AEDs) continue to be a major cause of drug withdrawals both in development and post-marketing. While liver-related AEDs are a major concern for drug safety, there are few in silico models for predicting human liver toxicity for drug candidates. We have applied the Quantitative Structure Activity Relationship (QSAR) approach to model liver AEDs. In this study, we aimed to construct a QSAR model capable of binary classification (active vs. inactive) of drugs for liver AEDs based on chemical structure. To build QSAR models, we have employed an FDA spontaneous reporting database of human liver AEDs (elevations in activity of serum liver enzymes), which contains data on approximately 500 approved drugs. Approximately 200 compounds with wide clinical data coverage, structural similarity and balanced (40/60) active/inactive ratio were selected for modeling and divided into multiple training/test and external validation sets. QSAR models were developed using the k nearest neighbor method and validated using external datasets. Models with high sensitivity (>73%) and specificity (>94%) for prediction of liver AEDs in external validation sets were developed. To test applicability of the models, three chemical databases (World Drug Index, Prestwick Chemical Library, and Biowisdom Liver Intelligence Module) were screened in silico and the validity of predictions was determined, where possible, by comparing model-based classification with assertions in publicly available literature. Validated QSAR models of liver AEDs based on the data from the FDA spontaneous reporting system can be employed as sensitive and specific predictors of AEDs in pre-clinical screening of drug candidates for potential hepatotoxicity in humans. PMID:20192250

Structure-based discovery and binding site analysis of histamine receptor ligands.

PubMed

Kiss, Róbert; Keserű, György M

2016-12-01

The application of structure-based drug discovery in histamine receptor projects was previously hampered by the lack of experimental structures. The publication of the first X-ray structure of the histamine H1 receptor has been followed by several successful virtual screens and binding site analysis studies of H1-antihistamines. This structure together with several other recently solved aminergic G-protein coupled receptors (GPCRs) enabled the development of more realistic homology models for H2, H3 and H4 receptors. Areas covered: In this paper, the authors review the development of histamine receptor models and their application in drug discovery. Expert opinion: In the authors' opinion, the application of atomistic histamine receptor models has played a significant role in understanding key ligand-receptor interactions as well as in the discovery of novel chemical starting points. The recently solved H1 receptor structure is a major milestone in structure-based drug discovery; however, our analysis also demonstrates that for building H3 and H4 receptor homology models, other GPCRs may be more suitable as templates. For these receptors, the authors envisage that the development of higher quality homology models will significantly contribute to the discovery and optimization of novel H3 and H4 ligands.

An emerging integration between ionic liquids and nanotechnology: general uses and future prospects in drug delivery.

PubMed

de Almeida, Tânia Santos; Júlio, Ana; Mota, Joana Portugal; Rijo, Patrícia; Reis, Catarina Pinto

2017-06-01

There is a growing need to develop drug-delivery systems that overcome drawbacks such as poor drug solubility/loading/release, systemic side effects and limited stability. Ionic liquids (ILs) offer many advantages and their tailoring represents a valuable tuning tool. Nano-based systems are also prized materials that prevent drug degradation, enhance their transport/distribution and extend their release. Consequently, structures containing ILs and nanoparticles (NPs) have been developed to attain synergistic effects. This overview on the properties of ILs, NPs and of their combined structures, reveals the recent advances in these areas through a review of pertinent literature. The IL-NP structures present enhanced properties and the subsequent performance upgrade proves to be useful in drug delivery, although much is yet to be done.

Latest development on RNA-based drugs and vaccines.

PubMed

Lundstrom, Kenneth

2018-06-01

Drugs and vaccines based on mRNA and RNA viruses show great potential and direct translation in the cytoplasm eliminates chromosomal integration. Limitations are associated with delivery and stability issues related to RNA degradation. Clinical trials on RNA-based drugs have been conducted in various disease areas. Likewise, RNA-based vaccines for viral infections and various cancers have been subjected to preclinical and clinical studies. RNA delivery and stability improvements include RNA structure modifications, targeting dendritic cells and employing self-amplifying RNA. Single-stranded RNA viruses possess self-amplifying RNA, which can provide extreme RNA replication in the cytoplasm to support RNA-based drug and vaccine development. Although oligonucleotide-based approaches have demonstrated potential, the focus here is on mRNA- and RNA virus-based methods.

From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-01-01

Fragment-based drug discovery (FBDD) is a broadly used strategy in structure-guided ligand design, whereby low-molecular weight hits move from lead-like to drug-like compounds. Over the past 15 years, an increasingly important role of the integration of these strategies into industrial and academic research platforms has been successfully established, allowing outstanding contributions to drug discovery. One important factor for the current prominence of FBDD is the better coverage of the chemical space provided by fragment-like libraries. The development of the field relies on two features: (i) the growing number of structurally characterized drug targets and (ii) the enormous chemical diversity available for experimental and virtual screenings. Indeed, fragment-based campaigns have contributed to address major challenges in lead optimization, such as the appropriate physicochemical profile of clinical candidates. This perspective paper outlines the usefulness and applications of FBDD approaches in medicinal chemistry and drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Potential of agricultural fungicides for antifungal drug discovery.

PubMed

Jampilek, Josef

2016-01-01

While it is true that only a small fraction of fungal species are responsible for human mycoses, the increasing prevalence of fungal diseases has highlighted an urgent need to develop new antifungal drugs, especially for systemic administration. This contribution focuses on the similarities between agricultural fungicides and drugs. Inorganic, organometallic and organic compounds can be found amongst agricultural fungicides. Furthermore, fungicides are designed and developed in a similar fashion to drugs based on similar rules and guidelines, with fungicides also having to meet similar criteria of lead-likeness and/or drug-likeness. Modern approved specific-target fungicides are well-characterized entities with a proposed structure-activity relationships hypothesis and a defined mode of action. Extensive toxicological evaluation, including mammalian toxicology assays, is performed during the whole discovery and development process. Thus modern agrochemical research (design of modern agrochemicals) comes close to drug design, discovery and development. Therefore, modern specific-target fungicides represent excellent lead-like structures/models for novel drug design and development.

Software and resources for computational medicinal chemistry

PubMed Central

Liao, Chenzhong; Sitzmann, Markus; Pugliese, Angelo; Nicklaus, Marc C

2011-01-01

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools. PMID:21707404

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description.

PubMed

Spyrakis, Francesca; Cavasotto, Claudio N

2015-10-01

Structure-based virtual screening is currently an established tool in drug lead discovery projects. Although in the last years the field saw an impressive progress in terms of algorithm development, computational performance, and retrospective and prospective applications in ligand identification, there are still long-standing challenges where further improvement is needed. In this review, we consider the conceptual frame, state-of-the-art and recent developments of three critical "structural" issues in structure-based drug lead discovery: the use of homology modeling to accurately model the binding site when no experimental structures are available, the necessity of accounting for the dynamics of intrinsically flexible systems as proteins, and the importance of considering active site water molecules in lead identification and optimization campaigns. Copyright © 2015 Elsevier Inc. All rights reserved.

X-ray and cryo-EM structures of inhibitor-bound cytochrome bc 1 complexes for structure-based drug discovery

PubMed Central

Amporndanai, Kangsa; O’Neill, Paul M.

2018-01-01

Cytochrome bc 1, a dimeric multi-subunit electron-transport protein embedded in the inner mitochondrial membrane, is a major drug target for the treatment and prevention of malaria and toxoplasmosis. Structural studies of cytochrome bc 1 from mammalian homologues co-crystallized with lead compounds have underpinned structure-based drug design to develop compounds with higher potency and selectivity. However, owing to the limited amount of cytochrome bc 1 that may be available from parasites, all efforts have been focused on homologous cytochrome bc 1 complexes from mammalian species, which has resulted in the failure of some drug candidates owing to toxicity in the host. Crystallographic studies of the native parasite proteins are not feasible owing to limited availability of the proteins. Here, it is demonstrated that cytochrome bc 1 is highly amenable to single-particle cryo-EM (which uses significantly less protein) by solving the apo and two inhibitor-bound structures to ∼4.1 Å resolution, revealing clear inhibitor density at the binding site. Therefore, cryo-EM is proposed as a viable alternative method for structure-based drug discovery using both host and parasite enzymes. PMID:29765610

Chemical Proteomics and Structural Biology Define EPHA2 Inhibition by Clinical Kinase Drugs.

PubMed

Heinzlmeir, Stephanie; Kudlinzki, Denis; Sreeramulu, Sridhar; Klaeger, Susan; Gande, Santosh Lakshmi; Linhard, Verena; Wilhelm, Mathias; Qiao, Huichao; Helm, Dominic; Ruprecht, Benjamin; Saxena, Krishna; Médard, Guillaume; Schwalbe, Harald; Kuster, Bernhard

2016-12-16

The receptor tyrosine kinase EPHA2 (Ephrin type-A receptor 2) plays important roles in oncogenesis, metastasis, and treatment resistance, yet therapeutic targeting, drug discovery, or investigation of EPHA2 biology is hampered by the lack of appropriate inhibitors and structural information. Here, we used chemical proteomics to survey 235 clinical kinase inhibitors for their kinase selectivity and identified 24 drugs with submicromolar affinities for EPHA2. NMR-based conformational dynamics together with nine new cocrystal structures delineated drug-EPHA2 interactions in full detail. The combination of selectivity profiling, structure determination, and kinome wide sequence alignment allowed the development of a classification system in which amino acids in the drug binding site of EPHA2 are categorized into key, scaffold, potency, and selectivity residues. This scheme should be generally applicable in kinase drug discovery, and we anticipate that the provided information will greatly facilitate the development of selective EPHA2 inhibitors in particular and the repurposing of clinical kinase inhibitors in general.

Protein crystallography and drug discovery: recollections of knowledge exchange between academia and industry

PubMed Central

2017-01-01

The development of structure-guided drug discovery is a story of knowledge exchange where new ideas originate from all parts of the research ecosystem. Dorothy Crowfoot Hodgkin obtained insulin from Boots Pure Drug Company in the 1930s and insulin crystallization was optimized in the company Novo in the 1950s, allowing the structure to be determined at Oxford University. The structure of renin was developed in academia, on this occasion in London, in response to a need to develop antihypertensives in pharma. The idea of a dimeric aspartic protease came from an international academic team and was discovered in HIV; it eventually led to new HIV antivirals being developed in industry. Structure-guided fragment-based discovery was developed in large pharma and biotechs, but has been exploited in academia for the development of new inhibitors targeting protein–protein interactions and also antimicrobials to combat mycobacterial infections such as tuberculosis. These observations provide a strong argument against the so-called ‘linear model’, where ideas flow only in one direction from academic institutions to industry. Structure-guided drug discovery is a story of applications of protein crystallography and knowledge exhange between academia and industry that has led to new drug approvals for cancer and other common medical conditions by the Food and Drug Administration in the USA, as well as hope for the treatment of rare genetic diseases and infectious diseases that are a particular challenge in the developing world. PMID:28875019

Structure-based drug design: aiming for a perfect fit

PubMed Central

van Montfort, Rob L.M.; Workman, Paul

2017-01-01

Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major progress made in fragment-based approaches for which success has been exemplified by over 30 clinical drug candidates and importantly three FDA-approved drugs in oncology. We summarize the articles in this issue that provide an excellent snapshot of the current state of the field of SBDD and fragment-based drug design and which offer key insights into exciting new developments, such as the X-ray free-electron laser technology, cryo-electron microscopy, open science approaches and targeted protein degradation. We stress the value of SBDD in the design of high-quality chemical tools that are used to interrogate biology and disease pathology, and to inform target validation. We emphasize the need to maintain the scientific rigour that has been traditionally associated with structural biology and extend this to other methods used in drug discovery. This is particularly important because the quality and robustness of any form of contributory data determines its usefulness in accelerating drug design, and therefore ultimately in providing patient benefit. PMID:29118091

A Structural Biology and Protein Engineering Approach to the Development of Antidotes against the Inhibition of Human Acetylcholinesterase by OP-based Nerve Agents

DTIC Science & Technology

2014-03-01

for Biotechnology, Gurgaon, India (Sep, 2013) by Joel L. Sussman, title: “Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function...Molecular Basis of How Nerve Agents through anti- Alzheimer Drugs Function: 3D Structure of Acetylcholinesterase • Florida International University...FIU), Miami, FL (Dec 2013) - Invited Lecture by Joel L. Sussman, title: “Molecular Basis of anti- Alzheimer Drugs & Nerve Agents: 3D Structure of

Protein crystallography and infectious diseases.

PubMed Central

Verlinde, C. L.; Merritt, E. A.; Van den Akker, F.; Kim, H.; Feil, I.; Delboni, L. F.; Mande, S. C.; Sarfaty, S.; Petra, P. H.; Hol, W. G.

1994-01-01

The current rapid growth in the number of known 3-dimensional protein structures is producing a database of structures that is increasingly useful as a starting point for the development of new medically relevant molecules such as drugs, therapeutic proteins, and vaccines. This development is beautifully illustrated in the recent book, Protein structure: New approaches to disease and therapy (Perutz, 1992). There is a great and growing promise for the design of molecules for the treatment or prevention of a wide variety of diseases, an endeavor made possible by the insights derived from the structure and function of crucial proteins from pathogenic organisms and from man. We present here 2 illustrations of structure-based drug design. The first is the prospect of developing antitrypanosomal drugs based on crystallographic, ligand-binding, and molecular modeling studies of glycolytic glycosomal enzymes from Trypanosomatidae. These unicellular organisms are responsible for several tropical diseases, including African and American trypanosomiases, as well as various forms of leishmaniasis. Because the target enzymes are also present in the human host, this project is a pioneering study in selective design. The second illustrative case is the prospect of designing anti-cholera drugs based on detailed analysis of the structure of cholera toxin and the closely related Escherichia coli heat-labile enterotoxin. Such potential drugs can be targeted either at inhibiting the toxin's receptor binding site or at blocking the toxin's intracellular catalytic activity. Study of the Vibrio cholerae and E. coli toxins serves at the same time as an example of a general approach to structure-based vaccine design. These toxins exhibit a remarkable ability to stimulate the mucosal immune system, and early results have suggested that this property can be maintained by engineered fusion proteins based on the native toxin structure. The challenge is thus to incorporate selected epitopes from foreign pathogens into the native framework of the toxin such that crucial features of both the epitope and the toxin are maintained. That is, the modified toxin must continue to evoke a strong mucosal immune response, and this response must be directed against an epitope conformation characteristic of the original pathogen. PMID:7849584

Computational predictive models for P-glycoprotein inhibition of in-house chalcone derivatives and drug-bank compounds.

PubMed

Ngo, Trieu-Du; Tran, Thanh-Dao; Le, Minh-Tri; Thai, Khac-Minh

2016-11-01

The human P-glycoprotein (P-gp) efflux pump is of great interest for medicinal chemists because of its important role in multidrug resistance (MDR). Because of the high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of this transmembrane protein, ligand-based, and structure-based approaches which were machine learning, homology modeling, and molecular docking were combined for this study. In ligand-based approach, individual two-dimensional quantitative structure-activity relationship models were developed using different machine learning algorithms and subsequently combined into the Ensemble model which showed good performance on both the diverse training set and the validation sets. The applicability domain and the prediction quality of the developed models were also judged using the state-of-the-art methods and tools. In our structure-based approach, the P-gp structure and its binding region were predicted for a docking study to determine possible interactions between the ligands and the receptor. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening using prediction models and molecular docking in an attempt to restore cancer cell sensitivity to cytotoxic drugs.

26th National Medicinal Chemistry Symposium--Developments in chemokines, carbohydrates, p53 and drug metabolism. 14-18 June 1998, Richmond, Virginia, USA.

PubMed

Swords, B

1998-08-01

This symposium, organized by the American Chemical Society, is held every two years. This year's meeting, sponsored by the ACS and The Virginia Commonwealth University, was attended by approximately 300 delegates and covered developments in chemokines, carbohydrates, p53, drug metabolism, prodrugs, structure-based design and molecular modeling. At the opening ceremony, John Topliss began by paying tribute to the distinguished medicinal chemistry career of Alfred Burger (University of Virginia, USA). He then reviewed the application of physicochemical principles to drug design, including the development and application of quantitative structure-activity relationship methodology.

Homology Modeling of Dopamine D2 and D3 Receptors: Molecular Dynamics Refinement and Docking Evaluation

PubMed Central

Platania, Chiara Bianca Maria; Salomone, Salvatore; Leggio, Gian Marco; Drago, Filippo; Bucolo, Claudio

2012-01-01

Dopamine (DA) receptors, a class of G-protein coupled receptors (GPCRs), have been targeted for drug development for the treatment of neurological, psychiatric and ocular disorders. The lack of structural information about GPCRs and their ligand complexes has prompted the development of homology models of these proteins aimed at structure-based drug design. Crystal structure of human dopamine D3 (hD3) receptor has been recently solved. Based on the hD3 receptor crystal structure we generated dopamine D2 and D3 receptor models and refined them with molecular dynamics (MD) protocol. Refined structures, obtained from the MD simulations in membrane environment, were subsequently used in molecular docking studies in order to investigate potential sites of interaction. The structure of hD3 and hD2L receptors was differentiated by means of MD simulations and D3 selective ligands were discriminated, in terms of binding energy, by docking calculation. Robust correlation of computed and experimental Ki was obtained for hD3 and hD2L receptor ligands. In conclusion, the present computational approach seems suitable to build and refine structure models of homologous dopamine receptors that may be of value for structure-based drug discovery of selective dopaminergic ligands. PMID:22970199

Molecular models of NS3 protease variants of the Hepatitis C virus.

PubMed

da Silveira, Nelson J F; Arcuri, Helen A; Bonalumi, Carlos E; de Souza, Fátima P; Mello, Isabel M V G C; Rahal, Paula; Pinho, João R R; de Azevedo, Walter F

2005-01-21

Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed. The atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures. This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.

Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

PubMed

Shanmugam, Anusuya; Natarajan, Jeyakumar

2012-06-01

Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

Computer-Aided Structure Based Drug Design Approaches for the Discovery of New Anti-CHIKV Agents.

PubMed

Jadav, Surender Singh; Sinha, Barij Nayan; Hilgenfeld, Rolf; Jayaprakash, Venkatesan

2017-11-10

Chikungunya is a viral infection caused by Chikungunya virus (CHIKV), an arbovirus transmitted through mosquito (Aedes aegypti and Aedes albopictus) bite. The virus from sylvatic cycle in Africa mutated to new vector adaptation and became one of the major emerging and re-emerging viral infections in the past decade, affecting more than 40 countries. Efforts are being made by many researches to develop means to prevent and control the infection through vaccines and vector control strategy. On the other hand, search for novel chemotherapeutic agents for the treatment of infected patients is on. Approach of repurposed drug is one way of identifying an existing drug for the treatment of CHIKV infection. Review the history of CHIKV nsp2 protease inhibitors derived through structure-based computer-aided drug design along with phytochemicals identified as anti-CHIKV agents. A survey on CHIKV inhibitors reported till date has been carriedout. The data obtained were organized and discussed under natural substances and synthetic derivatives obtained as result of rational design. The review provides a well organized content in chronological order that has highly significant information for medicinal chemist who wish to explore the area of Anti-CHIKV drug design and development. Natural compounds with different scaffolds provides an opportunity to explore Ligand based drug design (LBDD), while rational drug design approaches provides opportunity to explore the Structure based drug design. From the presented mini-review, readers can understand that this area is less explored and has lots of potential in anti-CHIKVviral drug design & development. of reported literature inferred that, unlike other viral proteases, the nsP2 protease can be targeted for CHIKV viral inhibition. The HTVS process for the identification of anti-CHIK agents provided a few successive validated lead compounds against CHIKV infections. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome

PubMed Central

Low, Yen S; Caster, Ola; Bergvall, Tomas; Fourches, Denis; Zang, Xiaoling; Norén, G Niklas; Rusyn, Ivan; Edwards, Ralph

2016-01-01

Objective Quantitative Structure-Activity Relationship (QSAR) models can predict adverse drug reactions (ADRs), and thus provide early warnings of potential hazards. Timely identification of potential safety concerns could protect patients and aid early diagnosis of ADRs among the exposed. Our objective was to determine whether global spontaneous reporting patterns might allow chemical substructures associated with Stevens-Johnson Syndrome (SJS) to be identified and utilized for ADR prediction by QSAR models. Materials and Methods Using a reference set of 364 drugs having positive or negative reporting correlations with SJS in the VigiBase global repository of individual case safety reports (Uppsala Monitoring Center, Uppsala, Sweden), chemical descriptors were computed from drug molecular structures. Random Forest and Support Vector Machines methods were used to develop QSAR models, which were validated by external 5-fold cross validation. Models were employed for virtual screening of DrugBank to predict SJS actives and inactives, which were corroborated using knowledge bases like VigiBase, ChemoText, and MicroMedex (Truven Health Analytics Inc, Ann Arbor, Michigan). Results We developed QSAR models that could accurately predict if drugs were associated with SJS (area under the curve of 75%–81%). Our 10 most active and inactive predictions were substantiated by SJS reports (or lack thereof) in the literature. Discussion Interpretation of QSAR models in terms of significant chemical descriptors suggested novel SJS structural alerts. Conclusions We have demonstrated that QSAR models can accurately identify SJS active and inactive drugs. Requiring chemical structures only, QSAR models provide effective computational means to flag potentially harmful drugs for subsequent targeted surveillance and pharmacoepidemiologic investigations. PMID:26499102

Structural Biology and the Design of New Therapeutics: From HIV and Cancer to Mycobacterial Infections: A Paper Dedicated to John Kendrew.

PubMed

Thomas, Sherine E; Mendes, Vitor; Kim, So Yeon; Malhotra, Sony; Ochoa-Montaño, Bernardo; Blaszczyk, Michal; Blundell, Tom L

2017-08-18

Interest in applications of protein crystallography to medicine was evident, as the first high-resolution structures emerged in the 50s and 60s. In Cambridge, Max Perutz and John Kendrew sought to understand mutations in sickle cell and other genetic diseases related to hemoglobin, while in Oxford, the group of Dorothy Hodgkin became interested in long-lasting zinc-insulin crystals for treatment of diabetes and later considered insulin redesign, as synthetic insulins became possible. The use of protein crystallography in structure-guided drug discovery emerged as enzyme structures allowed the identification of potential inhibitor-binding sites and optimization of interactions of hits using the structure of the target protein. Early examples of this approach were the use of the structure of renin to design antihypertensives and the structure of HIV protease in design of 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 and has been used to progress three oncology drugs through clinical trials to FDA approval. We exemplify current developments in structure-guided target identification and fragment-based lead discovery with efforts to develop new antimicrobials for mycobacterial infections. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The Development of a Korean Drug Dosing Database

PubMed Central

Kim, Sun Ah; Kim, Jung Hoon; Jang, Yoo Jin; Jeon, Man Ho; Hwang, Joong Un; Jeong, Young Mi; Choi, Kyung Suk; Lee, Iyn Hyang; Jeon, Jin Ok; Lee, Eun Sook; Lee, Eun Kyung; Kim, Hong Bin; Chin, Ho Jun; Ha, Ji Hye; Kim, Young Hoon

2011-01-01

Objectives This report describes the development process of a drug dosing database for ethical drugs approved by the Korea Food & Drug Administration (KFDA). The goal of this study was to develop a computerized system that supports physicians' prescribing decisions, particularly in regards to medication dosing. Methods The advisory committee, comprised of doctors, pharmacists, and nurses from the Seoul National University Bundang Hospital, pharmacists familiar with drug databases, KFDA officials, and software developers from the BIT Computer Co. Ltd. analyzed approved KFDA drug dosing information, defined the fields and properties of the information structure, and designed a management program used to enter dosing information. The management program was developed using a web based system that allows multiple researchers to input drug dosing information in an organized manner. The whole process was improved by adding additional input fields and eliminating the unnecessary existing fields used when the dosing information was entered, resulting in an improved field structure. Results A total of 16,994 drugs sold in the Korean market in July 2009, excluding the exclusion criteria (e.g., radioactivity drugs, X-ray contrast medium), usage and dosing information were made into a database. Conclusions The drug dosing database was successfully developed and the dosing information for new drugs can be continually maintained through the management mode. This database will be used to develop the drug utilization review standards and to provide appropriate dosing information. PMID:22259729

The future of crystallography in drug discovery

PubMed Central

Zheng, Heping; Hou, Jing; Zimmerman, Matthew D; Wlodawer, Alexander; Minor, Wladek

2014-01-01

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 these hypotheses. X-ray crystallography will find its future application in drug discovery by the development of specific tools that would allow realistic interpretation of the outcome coordinates and/or support testing of these hypotheses. PMID:24372145

Anti-infectious drug repurposing using an integrated chemical genomics and structural systems biology approach.

PubMed

Ng, Clara; Hauptman, Ruth; Zhang, Yinliang; Bourne, Philip E; Xie, Lei

2014-01-01

The emergence of multi-drug and extensive drug resistance of microbes to antibiotics poses a great threat to human health. Although drug repurposing is a promising solution for accelerating the drug development process, its application to anti-infectious drug discovery is limited by the scope of existing phenotype-, ligand-, or target-based methods. In this paper we introduce a new computational strategy to determine the genome-wide molecular targets of bioactive compounds in both human and bacterial genomes. Our method is based on the use of a novel algorithm, ligand Enrichment of Network Topological Similarity (ligENTS), to map the chemical universe to its global pharmacological space. ligENTS outperforms the state-of-the-art algorithms in identifying novel drug-target relationships. Furthermore, we integrate ligENTS with our structural systems biology platform to identify drug repurposing opportunities via target similarity profiling. Using this integrated strategy, we have identified novel P. falciparum targets of drug-like active compounds from the Malaria Box, and suggest that a number of approved drugs may be active against malaria. This study demonstrates the potential of an integrative chemical genomics and structural systems biology approach to drug repurposing.

Beyond 'peer pressure': rethinking drug use and 'youth culture'.

PubMed

Pilkington, Hilary

2007-05-01

The study of drug use by young people in the West has been transformed over the last decade by the development of sociological approaches to drug use which take serious account of the cultural context in which young people encounter drugs. One consequence is that the notion of 'peer pressure', as the primary articulation of the engagement between youth culture and drug use, has been displaced by that of 'normalisation', which envisages 'recreational' drug use as one expression of consumer-based youth cultural lifestyles. In stark contrast, academic discussion of drug use in Russia remains primarily concerned with the prevalence and health consequences of (intravenous) drug use while explanations of rising rates of drug use focus on structural factors related to the expansion of drugs supply and, to a lesser extent, post-Soviet social and economic dislocation. In this article, original empirical research in Russia is used to develop an understanding of young people's drug use that synthesises structural and cultural explanations of it. It does this by situating young people's narratives of their drugs choices in the context of local drugs markets and broader socio-economic processes. However, it attempts to go beyond seeing structural location as simply a 'constraint' on individual choice by adopting an understanding of 'youth culture' as a range of youth cultural practices and formations that simultaneously embody, reproduce and negotiate the structural locations of their subjects.

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

De novo design of molecular architectures by evolutionary assembly of drug-derived building blocks.

PubMed

Schneider, G; Lee, M L; Stahl, M; Schneider, P

2000-07-01

An evolutionary algorithm was developed for fragment-based de novo design of molecules (TOPAS, TOPology-Assigning System). This stochastic method aims at generating a novel molecular structure mimicking a template structure. A set of approximately 25,000 fragment structures serves as the building block supply, which were obtained by a straightforward fragmentation procedure applied to 36,000 known drugs. Eleven reaction schemes were implemented for both fragmentation and building block assembly. This combination of drug-derived building blocks and a restricted set of reaction schemes proved to be a key for the automatic development of novel, synthetically tractable structures. In a cyclic optimization process, molecular architectures were generated from a parent structure by virtual synthesis, and the best structure of a generation was selected as the parent for the subsequent TOPAS cycle. Similarity measures were used to define 'fitness', based on 2D-structural similarity or topological pharmacophore distance between the template molecule and the variants. The concept of varying library 'diversity' during a design process was consequently implemented by using adaptive variant distributions. The efficiency of the design algorithm was demonstrated for the de novo construction of potential thrombin inhibitors mimicking peptide and non-peptide template structures.

Combining functional and structural genomics to sample the essential Burkholderia structome.

PubMed

Baugh, Loren; Gallagher, Larry A; Patrapuvich, Rapatbhorn; Clifton, Matthew C; Gardberg, Anna S; Edwards, Thomas E; Armour, Brianna; Begley, Darren W; Dieterich, Shellie H; Dranow, David M; Abendroth, Jan; Fairman, James W; Fox, David; Staker, Bart L; Phan, Isabelle; Gillespie, Angela; Choi, Ryan; Nakazawa-Hewitt, Steve; Nguyen, Mary Trang; Napuli, Alberto; Barrett, Lynn; Buchko, Garry W; Stacy, Robin; Myler, Peter J; Stewart, Lance J; Manoil, Colin; Van Voorhis, Wesley C

2013-01-01

The genus Burkholderia includes pathogenic gram-negative bacteria that cause melioidosis, glanders, and pulmonary infections of patients with cancer and cystic fibrosis. Drug resistance has made development of new antimicrobials critical. Many approaches to discovering new antimicrobials, such as structure-based drug design and whole cell phenotypic screens followed by lead refinement, require high-resolution structures of proteins essential to the parasite. We experimentally identified 406 putative essential genes in B. thailandensis, a low-virulence species phylogenetically similar to B. pseudomallei, the causative agent of melioidosis, using saturation-level transposon mutagenesis and next-generation sequencing (Tn-seq). We selected 315 protein products of these genes based on structure-determination criteria, such as excluding very large and/or integral membrane proteins, and entered them into the Seattle Structural Genomics Center for Infection Disease (SSGCID) structure determination pipeline. To maximize structural coverage of these targets, we applied an "ortholog rescue" strategy for those producing insoluble or difficult to crystallize proteins, resulting in the addition of 387 orthologs (or paralogs) from seven other Burkholderia species into the SSGCID pipeline. This structural genomics approach yielded structures from 31 putative essential targets from B. thailandensis, and 25 orthologs from other Burkholderia species, yielding an overall structural coverage for 49 of the 406 essential gene families, with a total of 88 depositions into the Protein Data Bank. Of these, 25 proteins have properties of a potential antimicrobial drug target i.e., no close human homolog, part of an essential metabolic pathway, and a deep binding pocket. We describe the structures of several potential drug targets in detail. This collection of structures, solubility and experimental essentiality data provides a resource for development of drugs against infections and diseases caused by Burkholderia. All expression clones and proteins created in this study are freely available by request.

Creation of a Novel Class of Potent and Selective MutT Homologue 1 (MTH1) Inhibitors Using Fragment-Based Screening and Structure-Based Drug Design.

PubMed

Rahm, Fredrik; Viklund, Jenny; Trésaugues, Lionel; Ellermann, Manuel; Giese, Anja; Ericsson, Ulrika; Forsblom, Rickard; Ginman, Tobias; Günther, Judith; Hallberg, Kenth; Lindström, Johan; Persson, Lars Boukharta; Silvander, Camilla; Talagas, Antoine; Díaz-Sáez, Laura; Fedorov, Oleg; Huber, Kilian V M; Panagakou, Ioanna; Siejka, Paulina; Gorjánácz, Mátyás; Bauser, Marcus; Andersson, Martin

2018-03-22

Recent literature has both suggested and questioned MTH1 as a novel cancer target. BAY-707 was just published as a target validation small molecule probe for assessing the effects of pharmacological inhibition of MTH1 on tumor cell survival, both in vitro and in vivo. (1) In this report, we describe the medicinal chemistry program creating BAY-707, where fragment-based methods were used to develop a series of highly potent and selective MTH1 inhibitors. Using structure-based drug design and rational medicinal chemistry approaches, the potency was increased over 10,000 times from the fragment starting point while maintaining high ligand efficiency and drug-like properties.

Fragment-Based Drug Discovery in Academia: Experiences From a Tuberculosis Programme

NASA Astrophysics Data System (ADS)

Heikkila, Timo J.; Surade, Sachin; Silvestre, Hernani L.; Dias, Marcio V. B.; Ciulli, Alessio; Bromfield, Karen; Scott, Duncan; Howard, Nigel; Wen, Shijun; Wei, Alvin Hung; Osborne, David; Abell, Chris; Blundell, Tom L.

The problems associated with neglected diseases are often compounded by increasing incidence of antibiotic resistance. Patient negligence and abuse of antibiotics has lead to explosive growth in cases of tuberculosis, with some M. tuberculosis strains becoming virtually untreatable. Structure-based drug development is viewed as cost-effective and time-consuming method for discovery and development of hits to lead compounds. In this review we will discuss the suitability of fragment-based methods for developing new chemotherapeutics against neglected diseases, providing examples from our tuberculosis programme.

Recent developments with metalloprotease inhibitor class of drug candidates for Botulinum neurotoxins

DOE PAGES

Kumar, Gyanendra; Swaminathan, Subramanyam

2015-03-01

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are also potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, andmore » these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.« less

Recent developments with metalloprotease inhibitor class of drug candidates for botulinum neurotoxins.

PubMed

Kumar, Gyanendra; Swaminathan, Subramanyam

2015-01-01

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, and these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.

Computational approaches for drug discovery.

PubMed

Hung, Che-Lun; Chen, Chi-Chun

2014-09-01

Cellular proteins are the mediators of multiple organism functions being involved in physiological mechanisms and disease. By discovering lead compounds that affect the function of target proteins, the target diseases or physiological mechanisms can be modulated. Based on knowledge of the ligand-receptor interaction, the chemical structures of leads can be modified to improve efficacy, selectivity and reduce side effects. One rational drug design technology, which enables drug discovery based on knowledge of target structures, functional properties and mechanisms, is computer-aided drug design (CADD). The application of CADD can be cost-effective using experiments to compare predicted and actual drug activity, the results from which can used iteratively to improve compound properties. The two major CADD-based approaches are structure-based drug design, where protein structures are required, and ligand-based drug design, where ligand and ligand activities can be used to design compounds interacting with the protein structure. Approaches in structure-based drug design include docking, de novo design, fragment-based drug discovery and structure-based pharmacophore modeling. Approaches in ligand-based drug design include quantitative structure-affinity relationship and pharmacophore modeling based on ligand properties. Based on whether the structure of the receptor and its interaction with the ligand are known, different design strategies can be seed. After lead compounds are generated, the rule of five can be used to assess whether these have drug-like properties. Several quality validation methods, such as cost function analysis, Fisher's cross-validation analysis and goodness of hit test, can be used to estimate the metrics of different drug design strategies. To further improve CADD performance, multi-computers and graphics processing units may be applied to reduce costs. © 2014 Wiley Periodicals, Inc.

TaxKB: a knowledge base for new taxane-related drug discovery.

PubMed

Murugan, Kasi; Shanmugasamy, Sangeetha; Al-Sohaibani, Saleh; Vignesh, Naga; Palanikannan, Kandavel; Vimala, Antonydhason; Kumar, Gopal Ramesh

2015-01-01

Taxanes are naturally occurring compounds which belong to a powerful group of chemotherapeutic drugs with anticancer properties. Their current use, clinical efficacy, and unique mechanism of action indicate their potentiality for cancer drug discovery and development thereby promising to reduce the high economy associated with cancer worldwide. Extensive research has been carried out on taxanes with the aim to combat issues of drug resistance, side effects, limited natural supply, and also to increase the therapeutic index of these molecules. These efforts have led to the isolation of many naturally occurring compounds belonging to this family (more than 350 different kinds), and the synthesis of semisynthetic analogs of the naturally existing molecules (>500), and has also led to the characterization of many (>1000) of them. A web-based database system on clinically exploitable taxanes, providing a link between the structure and the pharmacological property of these molecules could help to reduce the druggability gap for these molecules. Taxane knowledge base (TaxKB, http://bioinfo.au-kbc.org.in/taxane/Taxkb/), is an online multi-tier relational database that currently holds data on 42 parameters of 250 natural and 503 semisynthetic analogs of taxanes. This database provides researchers with much-needed information necessary for drug development. TaxKB enables the user to search data on the structure, drug-likeness, and physicochemical properties of both natural and synthetic taxanes with a "General Search" option in addition to a "Parameter Specific Search." It displays 2D structure and allows the user to download the 3D structure (a PDB file) of taxanes that can be viewed with any molecular visualization tool. The ultimate aim of TaxKB is to provide information on Absorption, Distribution, Metabolism, and Excretion/Toxicity (ADME/T) as well as data on bioavailability and target interaction properties of candidate anticancer taxanes, ahead of expensive clinical trials. This first web-based single-information portal will play a central role and help researchers to move forward in taxane-based cancer drug research.

Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review

PubMed Central

Csermely, Peter; Korcsmáros, Tamás; Kiss, Huba J.M.; London, Gábor; Nussinov, Ruth

2013-01-01

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

West Nile Virus Drug Discovery

PubMed Central

Lim, Siew Pheng; Shi, Pei-Yong

2013-01-01

The outbreak of West Nile virus (WNV) in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development. PMID:24300672

West Nile virus drug discovery.

PubMed

Lim, Siew Pheng; Shi, Pei-Yong

2013-12-03

The outbreak of West Nile virus (WNV) in 1999 in the USA, and its continued spread throughout the Americas, parts of Europe, the Middle East and Africa, underscored the need for WNV antiviral development. Here, we review the current status of WNV drug discovery. A number of approaches have been used to search for inhibitors of WNV, including viral infection-based screening, enzyme-based screening, structure-based virtual screening, structure-based rationale design, and antibody-based therapy. These efforts have yielded inhibitors of viral or cellular factors that are critical for viral replication. For small molecule inhibitors, no promising preclinical candidate has been developed; most of the inhibitors could not even be advanced to the stage of hit-to-lead optimization due to their poor drug-like properties. However, several inhibitors developed for related members of the family Flaviviridae, such as dengue virus and hepatitis C virus, exhibited cross-inhibition of WNV, suggesting the possibility to re-purpose these antivirals for WNV treatment. Most promisingly, therapeutic antibodies have shown excellent efficacy in mouse model; one of such antibodies has been advanced into clinical trial. The knowledge accumulated during the past fifteen years has provided better rationale for the ongoing WNV and other flavivirus antiviral development.

Fragment-based approaches to TB drugs.

PubMed

Marchetti, Chiara; Chan, Daniel S H; Coyne, Anthony G; Abell, Chris

2018-02-01

Tuberculosis is an infectious disease associated with significant mortality and morbidity worldwide, particularly in developing countries. The rise of antibiotic resistance in Mycobacterium tuberculosis (Mtb) urgently demands the development of new drug leads to tackle resistant strains. Fragment-based methods have recently emerged at the forefront of pharmaceutical development as a means to generate more effective lead structures, via the identification of fragment molecules that form weak but high quality interactions with the target biomolecule and subsequent fragment optimization. This review highlights a number of novel inhibitors of Mtb targets that have been developed through fragment-based approaches in recent years.

Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

PubMed

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling complex relationships between robustness of targeted kinase genes and binding specificity of targeted kinase drugs. We discuss how these approaches can exploit advances in chemical biology and network science to develop novel strategies for rationally tailored and robust personalized drug therapies.

Impact of computational structure-based methods on drug discovery.

PubMed

Reynolds, Charles H

2014-01-01

Structure-based drug design has become an indispensible tool in drug discovery. The emergence of structure-based design is due to gains in structural biology that have provided exponential growth in the number of protein crystal structures, new computational algorithms and approaches for modeling protein-ligand interactions, and the tremendous growth of raw computer power in the last 30 years. Computer modeling and simulation have made major contributions to the discovery of many groundbreaking drugs in recent years. Examples are presented that highlight the evolution of computational structure-based design methodology, and the impact of that methodology on drug discovery.

Functionalization of protein-based nanocages for drug delivery applications.

PubMed

Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.

A perspective on targeting non-structural proteins to combat neglected tropical diseases: Dengue, West Nile and Chikungunya viruses.

PubMed

Bhakat, Soumendranath; Karubiu, Wilson; Jayaprakash, Venkatesan; Soliman, Mahmoud E S

2014-11-24

Neglected tropical diseases are major causes of fatality in poverty stricken regions across Africa, Asia and some part of America. The combined potential health risk associated with arthropod-borne viruses (arboviruses); Dengue virus (DENV), West Nile Virus (WNV) and Chikungunya Virus (CHIKV) is immense. These arboviruses are either emerging or re-emerging in many regions with recent documented outbreaks in the United States. Despite several recent evidences of emergence, currently there are no approved drugs or vaccines available to counter these diseases. Non-structural proteins encoded by these RNA viruses are essential for their replication and maturation and thus may offer ideal targets for developing antiviral drugs. In recent years, several protease inhibitors have been sourced from plant extract, synthesis, computer aided drug design and high throughput screening as well as through drug reposition based approaches to target the non-structural proteins. The protease inhibitors have shown different levels of inhibition and may thus provide template to develop selective and potent drugs against these devastating arboviruses. This review seeks to shed light on the design and development of antiviral drugs against DENV, WNV and CHIKV to date. To the best of our knowledge, this review provides the first comprehensive update on the development of protease inhibitors targeting non-structural proteins of three most devastating arboviruses, DENV, WNV and CHIKV. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Multi-target parallel processing approach for gene-to-structure determination of the influenza polymerase PB2 subunit.

PubMed

Armour, Brianna L; Barnes, Steve R; Moen, Spencer O; Smith, Eric; Raymond, Amy C; Fairman, James W; Stewart, Lance J; Staker, Bart L; Begley, Darren W; Edwards, Thomas E; Lorimer, Donald D

2013-06-28

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year (1). Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans (2). Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains.

Informatic innovations in glycobiology: relevance to drug discovery.

PubMed

Mamitsuka, Hiroshi

2008-02-01

The recent development and applications of tree-based informatics on glycans have accelerated the biological analysis on glycans, particularly from structural viewpoints. We review three major aspects of recent informatics innovations on glycan structures: maturity of well-organized databases on glycan structures linking with other biological information, implementation of glycan structure matching algorithms and extensive development of methods for mining frequent patterns from glycan structures.

A receptor-grounded approach to teaching nonsteroidal antiinflammatory drug chemistry and structure-activity relationships.

PubMed

Roche, Victoria F

2009-12-17

To describe a receptor-based approach to promote learning about nonsteroidal anti-inflammatory drug (NSAID) chemistry, structure-activity relationships, and therapeutic decision-making. Three lessons on cyclooxygenase (COX) and NSAID chemistry, and NSAID therapeutic utility, were developed using text-based resources and primary medicinal chemistry and pharmacy practice literature. Learning tools were developed to assist students in content mastery. Student learning was evaluated via performance on quizzes and examinations that measured understanding of COX and NSAID chemistry, and the application of that knowledge to therapeutic problem solving. Student performance on NSAID-focused quizzes and examinations documented the success of this approach.

pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures

PubMed Central

2015-01-01

Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties. PMID:25860834

Quantitative self-assembly prediction yields targeted nanomedicines

NASA Astrophysics Data System (ADS)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

Using in Vitro Evolution and Whole Genome Analysis To Discover Next Generation Targets for Antimalarial Drug Discovery

PubMed Central

2018-01-01

Although many new anti-infectives have been discovered and developed solely using phenotypic cellular screening and assay optimization, most researchers recognize that structure-guided drug design is more practical and less costly. In addition, a greater chemical space can be interrogated with structure-guided drug design. The practicality of structure-guided drug design has launched a search for the targets of compounds discovered in phenotypic screens. One method that has been used extensively in malaria parasites for target discovery and chemical validation is in vitro evolution and whole genome analysis (IVIEWGA). Here, small molecules from phenotypic screens with demonstrated antiparasitic activity are used in genome-based target discovery methods. In this Review, we discuss the newest, most promising druggable targets discovered or further validated by evolution-based methods, as well as some exceptions. PMID:29451780

Strategies for the Optimization of Natural Leads to Anticancer Drugs or Drug Candidates

PubMed Central

Xiao, Zhiyan; Morris-Natschke, Susan L.; Lee, Kuo-Hsiung

2015-01-01

Natural products have made significant contribution to cancer chemotherapy over the past decades and remain an indispensable source of molecular and mechanistic diversity for anticancer drug discovery. More often than not, natural products may serve as leads for further drug development rather than as effective anticancer drugs by themselves. Generally, optimization of natural leads into anticancer drugs or drug candidates should not only address drug efficacy, but also improve ADMET profiles and chemical accessibility associated with the natural leads. Optimization strategies involve direct chemical manipulation of functional groups, structure-activity relationship-directed optimization and pharmacophore-oriented molecular design based on the natural templates. Both fundamental medicinal chemistry principles (e.g., bio-isosterism) and state-of-the-art computer-aided drug design techniques (e.g., structure-based design) can be applied to facilitate optimization efforts. In this review, the strategies to optimize natural leads to anticancer drugs or drug candidates are illustrated with examples and described according to their purposes. Furthermore, successful case studies on lead optimization of bioactive compounds performed in the Natural Products Research Laboratories at UNC are highlighted. PMID:26359649

Development of a 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, docking, and structure-based pharmacophore approaches - Conference Abstract

EPA Science Inventory

Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based appr...

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

PubMed

Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

Exploring the Role of Receptor Flexibility in Structure-Based Drug Discovery

PubMed Central

Feixas, Ferran; Lindert, Steffen; Sinko, William; McCammon, J. Andrew

2015-01-01

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

In silico modeling to predict drug-induced phospholipidosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

2013-06-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

The Structures of Life

ERIC Educational Resources Information Center

National Institute of General Medical Sciences (NIGMS), 2007

2007-01-01

This booklet reveals how structural biology provides insight into health and disease and is useful in developing new medications. It contains a general introduction to proteins, coverage of the techniques used to determine protein structures, and a chapter on structure-based drug design. The booklet features "Student Snapshots," designed to…

Effects of HIV-1 protease on cellular functions and their potential applications in antiretroviral therapy

PubMed Central

2012-01-01

Human Immunodeficiency Virus Type 1 (HIV-1) protease inhibitors (PIs) are the most potent class of drugs in antiretroviral therapies. However, viral drug resistance to PIs could emerge rapidly thus reducing the effectiveness of those drugs. Of note, all current FDA-approved PIs are competitive inhibitors, i.e., inhibitors that compete with substrates for the active enzymatic site. This common inhibitory approach increases the likelihood of developing drug resistant HIV-1 strains that are resistant to many or all current PIs. Hence, new PIs that move away from the current target of the active enzymatic site are needed. Specifically, allosteric inhibitors, inhibitors that prohibit PR enzymatic activities through non-competitive binding to PR, should be sought. Another common feature of current PIs is they were all developed based on the structure-based design. Drugs derived from a structure-based strategy may generate target specific and potent inhibitors. However, this type of drug design can only target one site at a time and drugs discovered by this method are often associated with strong side effects such as cellular toxicity, limiting its number of target choices, efficacy, and applicability. In contrast, a cell-based system may provide a useful alternative strategy that can overcome many of the inherited shortcomings associated with structure-based drug designs. For example, allosteric PIs can be sought using a cell-based system without considering the site or mechanism of inhibition. In addition, a cell-based system can eliminate those PIs that have strong cytotoxic effect. Most importantly, a simple, economical, and easy-to-maintained eukaryotic cellular system such as yeast will allow us to search for potential PIs in a large-scaled high throughput screening (HTS) system, thus increasing the chances of success. Based on our many years of experience in using fission yeast as a model system to study HIV-1 Vpr, we propose the use of fission yeast as a possible surrogate system to study the effects of HIV-1 protease on cellular functions and to explore its utility as a HTS system to search for new PIs to battle HIV-1 resistant strains. PMID:22971934

[Strategy for the development of dipeptide drugs].

PubMed

Gudasheva, T A

2011-01-01

The author describes an original approach to the development of dipeptide drugs based on the concept of the leading role of the beta-bend in the interaction of biologically active endogenous peptides with their receptors. The approach called "peptide-based drug design" includes both developments from the structure of a known psychotropic agent toward its topological peptide analog and developments from the active dipeptide site of a neuropeptide toward its mimetic. This strategy has been worked out at the V.V. Zakusov Research Institute of Pharmacology for 25 years. Results of investigations that discovered endogenous peptide prototypes of the known non-peptidic drugs (piracetam and sulpiride) are presented. They provided a basis for the creation of highly active non-toxic oral dipeptide preparations, such as nootrop Noopept, potential anti psychotic Dilept, and potential selective anxiolytic GB-115.

Development and application of hybrid structure based method for efficient screening of ligands binding to G-protein coupled receptors

NASA Astrophysics Data System (ADS)

Kortagere, Sandhya; Welsh, William J.

2006-12-01

G-protein coupled receptors (GPCRs) comprise a large superfamily of proteins that are targets for nearly 50% of drugs in clinical use today. In the past, the use of structure-based drug design strategies to develop better drug candidates has been severely hampered due to the absence of the receptor's three-dimensional structure. However, with recent advances in molecular modeling techniques and better computing power, atomic level details of these receptors can be derived from computationally derived molecular models. Using information from these models coupled with experimental evidence, it has become feasible to build receptor pharmacophores. In this study, we demonstrate the use of the Hybrid Structure Based (HSB) method that can be used effectively to screen and identify prospective ligands that bind to GPCRs. Essentially; this multi-step method combines ligand-based methods for building enriched libraries of small molecules and structure-based methods for screening molecules against the GPCR target. The HSB method was validated to identify retinal and its analogues from a random dataset of ˜300,000 molecules. The results from this study showed that the 9 top-ranking molecules are indeed analogues of retinal. The method was also tested to identify analogues of dopamine binding to the dopamine D2 receptor. Six of the ten top-ranking molecules are known analogues of dopamine including a prodrug, while the other thirty-four molecules are currently being tested for their activity against all dopamine receptors. The results from both these test cases have proved that the HSB method provides a realistic solution to bridge the gap between the ever-increasing demand for new drugs to treat psychiatric disorders and the lack of efficient screening methods for GPCRs.

Successful generation of structural information for fragment-based drug discovery.

PubMed

Öster, Linda; Tapani, Sofia; Xue, Yafeng; Käck, Helena

2015-09-01

Fragment-based drug discovery relies upon structural information for efficient compound progression, yet it is often challenging to generate structures with bound fragments. A summary of recent literature reveals that a wide repertoire of experimental procedures is employed to generate ligand-bound crystal structures successfully. We share in-house experience from setting up and executing fragment crystallography in a project that resulted in 55 complex structures. The ligands span five orders of magnitude in affinity and the resulting structures are made available to be of use, for example, for development of computational methods. Analysis of the results revealed that ligand properties such as potency, ligand efficiency (LE) and, to some degree, clogP influence the success of complex structure generation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving the apo-state detergent stability of NTS1 with CHESS for pharmacological and structural studies.

PubMed

Scott, Daniel J; Kummer, Lutz; Egloff, Pascal; Bathgate, Ross A D; Plückthun, Andreas

2014-11-01

The largest single class of drug targets is the G protein-coupled receptor (GPCR) family. Modern high-throughput methods for drug discovery require working with pure protein, but this has been a challenge for GPCRs, and thus the success of screening campaigns targeting soluble, catalytic protein domains has not yet been realized for GPCRs. Therefore, most GPCR drug screening has been cell-based, whereas the strategy of choice for drug discovery against soluble proteins is HTS using purified proteins coupled to structure-based drug design. While recent developments are increasing the chances of obtaining GPCR crystal structures, the feasibility of screening directly against purified GPCRs in the unbound state (apo-state) remains low. GPCRs exhibit low stability in detergent micelles, especially in the apo-state, over the time periods required for performing large screens. Recent methods for generating detergent-stable GPCRs, however, offer the potential for researchers to manipulate GPCRs almost like soluble enzymes, opening up new avenues for drug discovery. Here we apply cellular high-throughput encapsulation, solubilization and screening (CHESS) to the neurotensin receptor 1 (NTS1) to generate a variant that is stable in the apo-state when solubilized in detergents. This high stability facilitated the crystal structure determination of this receptor and also allowed us to probe the pharmacology of detergent-solubilized, apo-state NTS1 using robotic ligand binding assays. NTS1 is a target for the development of novel antipsychotics, and thus CHESS-stabilized receptors represent exciting tools for drug discovery. Copyright © 2014 Elsevier B.V. All rights reserved.

Small Scaffolds, Big Potential: Developing Miniature Proteins as Therapeutic Agents.

PubMed

Holub, Justin M

2017-09-01

Preclinical Research Miniature proteins are a class of oligopeptide characterized by their short sequence lengths and ability to adopt well-folded, three-dimensional structures. Because of their biomimetic nature and synthetic tractability, miniature proteins have been used to study a range of biochemical processes including fast protein folding, signal transduction, catalysis and molecular transport. Recently, miniature proteins have been gaining traction as potential therapeutic agents because their small size and ability to fold into defined tertiary structures facilitates their development as protein-based drugs. This research overview discusses emerging developments involving the use of miniature proteins as scaffolds to design novel therapeutics for the treatment and study of human disease. Specifically, this review will explore strategies to: (i) stabilize miniature protein tertiary structure; (ii) optimize biomolecular recognition by grafting functional epitopes onto miniature protein scaffolds; and (iii) enhance cytosolic delivery of miniature proteins through the use of cationic motifs that facilitate endosomal escape. These objectives are discussed not only to address challenges in developing effective miniature protein-based drugs, but also to highlight the tremendous potential miniature proteins hold for combating and understanding human disease. Drug Dev Res 78 : 268-282, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

In silico prediction of cytochrome P450-mediated drug metabolism.

PubMed

Zhang, Tao; Chen, Qi; Li, Li; Liu, Limin Angela; Wei, Dong-Qing

2011-06-01

The application of combinatorial chemistry and high-throughput screening technique enables the large number of chemicals to be generated and tested simultaneously, which will facilitate the drug development and discovery. At the same time, it brings about a challenge of how to efficiently identify the potential drug candidates from thousands of compounds. A way used to deal with the challenge is to consider the drug pharmacokinetic properties, such as absorption, distribution, metabolism and excretion (ADME), in the early stage of drug development. Among ADME properties, metabolism is of importance due to the strong association with efficacy and safety of drug. The review will focus on in silico approaches for prediction of Cytochrome P450-mediated drug metabolism. We will describe these predictive methods from two aspects, structure-based and data-based. Moreover, the applications and limitations of various methods will be discussed. Finally, we provide further direction toward improving the predictive accuracy of these in silico methods.

Porous starch-based drug delivery systems processed by a microwave route.

PubMed

Malafaya, P B; Elvira, C; Gallardo, A; San Román, J; Reis, R L

2001-01-01

Abstract-A new simple processing route to produce starch-based porous materials was developed based on a microwave baking methodology. This innovative processing route was used to obtain non-loaded controls and loaded drug delivery carriers, incorporating a non-steroid anti-inflammatory agent. This bioactive agent was selected as model drug with expectations that the developed methodology might be used for other drugs and growth factors. The prepared systems were characterized by 1H and 13C NMR spectroscopy which allow the study of the interactions between the starch-based materials and the processing components, i.e, the blowing agents. The porosity of the prepared materials was estimated by measuring their apparent density and studied by comparing drug-loaded and non-loaded carriers. The behaviour of the porous structures, while immersed in aqueous media, was studied in terms of swelling and degradation, being intimately related to their porosity. Finally, in vitro drug release studies were performed showing a clear burst effect, followed by a slow controlled release of the drug over several days (up to 10 days).

Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus.

PubMed

Wang, Jing-Fang; Wei, Dong-Qing; Chou, Kuo-Chen

2009-10-16

The M2 proton channel is one of indispensable components for the influenza A virus that plays a vital role in its life cycle and hence is an important target for drug design against the virus. In view of this, the three-dimensional structure of the H1N1-M2 channel was developed based on the primary sequence taken from a patient recently infected by the H1N1 (swine flu) virus. With an explicit water-membrane environment, molecular docking studies were performed for amantadine and rimantadine, the two commercial drugs generally used to treat influenza A infection. It was found that their binding affinity to the H1N1-M2 channel is significantly lower than that to the H5N1-M2 channel, fully consistent with the recent report that the H1N1 swine virus was resistant to the two drugs. The findings and the relevant analysis reported here might provide useful structural insights for developing effective drugs against the new swine flu virus.

Structure of the Angiotensin Receptor Revealed by Serial Femtosecond Crystallography

DOE PAGES

Zhang, Haitao; Unal, Hamiyet; Gati, Cornelius; ...

2015-05-07

We report that angiotensin II type 1 receptor (AT 1R) is a G protein-coupled receptor that serves as a primary regulator for blood pressure maintenance. Although several anti-hypertensive drugs have been developed as AT 1R blockers (ARBs), the structural basis for AT 1R ligand-binding and regulation has remained elusive, mostly due to the difficulties of growing high quality crystals for structure determination using synchrotron radiation. By applying the recently developed method of serial femtosecond crystallography at an X-ray free-electron laser, we successfully determined the room-temperature crystal structure of the human AT 1R in complex with its selective antagonist ZD7155 atmore » 2.9 Å resolution. The AT 1R-ZD7155 complex structure revealed key structural features ofAT 1R and critical interactions for ZD7155 binding. Finally, docking simulations of the clinically used ARBs into the AT 1R structure further elucidated both the common and distinct binding modes for these anti-hypertensive drugs. Our results thereby provide fundamental insights into AT 1R structure-function relationship and structure-based drug design.« less

Structure of the Angiotensin Receptor Revealed by Serial Femtosecond Crystallography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Haitao; Unal, Hamiyet; Gati, Cornelius

We report that angiotensin II type 1 receptor (AT 1R) is a G protein-coupled receptor that serves as a primary regulator for blood pressure maintenance. Although several anti-hypertensive drugs have been developed as AT 1R blockers (ARBs), the structural basis for AT 1R ligand-binding and regulation has remained elusive, mostly due to the difficulties of growing high quality crystals for structure determination using synchrotron radiation. By applying the recently developed method of serial femtosecond crystallography at an X-ray free-electron laser, we successfully determined the room-temperature crystal structure of the human AT 1R in complex with its selective antagonist ZD7155 atmore » 2.9 Å resolution. The AT 1R-ZD7155 complex structure revealed key structural features ofAT 1R and critical interactions for ZD7155 binding. Finally, docking simulations of the clinically used ARBs into the AT 1R structure further elucidated both the common and distinct binding modes for these anti-hypertensive drugs. Our results thereby provide fundamental insights into AT 1R structure-function relationship and structure-based drug design.« less

Triclosan Derivatives: Towards Potent Inhibitors of Drug-Sensitive and Drug-Resistant Mycobacterium tuberculosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Freundlich, Joel S.; Wang, Feng; Vilchèze, Catherine

Isoniazid (INH) is a frontline antitubercular drug that inhibits the enoyl acyl carrier protein reductase InhA. Novel inhibitors of InhA that are not cross-resistant to INH represent a significant goal in antitubercular chemotherapy. The design, synthesis, and biological activity of a series of triclosan-based inhibitors is reported, including their promising efficacy against INH-resistant strains of M. tuberculosis. Triclosan has been previously shown to inhibit InhA, an essential enoyl acyl carrier protein reductase involved in mycolic acid biosynthesis, the inhibition of which leads to the lysis of Mycobacterium tuberculosis. Using a structure-based drug design approach, a series of 5-substituted triclosan derivativesmore » was developed. Two groups of derivatives with alkyl and aryl substituents, respectively, were identified with dramatically enhanced potency against purified InhA. The most efficacious inhibitor displayed an IC{sub 50} value of 21 nM, which was 50-fold more potent than triclosan. X-ray crystal structures of InhA in complex with four triclosan derivatives revealed the structural basis for the inhibitory activity. Six selected triclosan derivatives were tested against isoniazid-sensitive and resistant strains of M. tuberculosis. Among those, the best inhibitor had an MIC value of 4.7 {mu}g mL{sup -1} (13 {mu}M), which represents a tenfold improvement over the bacteriocidal activity of triclosan. A subset of these triclosan analogues was more potent than isoniazid against two isoniazid-resistant M. tuberculosis strains, demonstrating the significant potential for structure-based design in the development of next generation antitubercular drugs.« less

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

PubMed Central

Moen, Spencer O.; Smith, Eric; Raymond, Amy C.; Fairman, James W.; Stewart, Lance J.; Staker, Bart L.; Begley, Darren W.; Edwards, Thomas E.; Lorimer, Donald D.

2013-01-01

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year 1. Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans 2. Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains. PMID:23851357

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein Footprinting

PubMed Central

Wang, Liwen; Chance, Mark R.

2011-01-01

Structural MS is a rapidly growing field with many applications in basic research and pharmaceutical drug development. In this feature article the overall technology is described and several examples of how hydroxyl radical based footprinting MS can be used to map interfaces, evaluate protein structure, and identify ligand dependent conformational changes in proteins are described. PMID:21770468

A Receptor-Grounded Approach to Teaching Nonsteroidal Antiinflammatory Drug Chemistry and Structure-Activity Relationships

PubMed Central

2009-01-01

Objective To describe a receptor-based approach to promote learning about nonsteroidal anti-inflammatory drug (NSAID) chemistry, structure-activity relationships, and therapeutic decision-making. Design Three lessons on cyclooxygenase (COX) and NSAID chemistry, and NSAID therapeutic utility, were developed using text-based resources and primary medicinal chemistry and pharmacy practice literature. Learning tools were developed to assist students in content mastery. Assessment Student learning was evaluated via performance on quizzes and examinations that measured understanding of COX and NSAID chemistry, and the application of that knowledge to therapeutic problem solving. Conclusion Student performance on NSAID-focused quizzes and examinations documented the success of this approach. PMID:20221336

Combining Functional and Structural Genomics to Sample the Essential Burkholderia Structome

PubMed Central

Baugh, Loren; Gallagher, Larry A.; Patrapuvich, Rapatbhorn; Clifton, Matthew C.; Gardberg, Anna S.; Edwards, Thomas E.; Armour, Brianna; Begley, Darren W.; Dieterich, Shellie H.; Dranow, David M.; Abendroth, Jan; Fairman, James W.; Fox, David; Staker, Bart L.; Phan, Isabelle; Gillespie, Angela; Choi, Ryan; Nakazawa-Hewitt, Steve; Nguyen, Mary Trang; Napuli, Alberto; Barrett, Lynn; Buchko, Garry W.; Stacy, Robin; Myler, Peter J.; Stewart, Lance J.; Manoil, Colin; Van Voorhis, Wesley C.

2013-01-01

Background The genus Burkholderia includes pathogenic gram-negative bacteria that cause melioidosis, glanders, and pulmonary infections of patients with cancer and cystic fibrosis. Drug resistance has made development of new antimicrobials critical. Many approaches to discovering new antimicrobials, such as structure-based drug design and whole cell phenotypic screens followed by lead refinement, require high-resolution structures of proteins essential to the parasite. Methodology/Principal Findings We experimentally identified 406 putative essential genes in B. thailandensis, a low-virulence species phylogenetically similar to B. pseudomallei, the causative agent of melioidosis, using saturation-level transposon mutagenesis and next-generation sequencing (Tn-seq). We selected 315 protein products of these genes based on structure-determination criteria, such as excluding very large and/or integral membrane proteins, and entered them into the Seattle Structural Genomics Center for Infection Disease (SSGCID) structure determination pipeline. To maximize structural coverage of these targets, we applied an “ortholog rescue” strategy for those producing insoluble or difficult to crystallize proteins, resulting in the addition of 387 orthologs (or paralogs) from seven other Burkholderia species into the SSGCID pipeline. This structural genomics approach yielded structures from 31 putative essential targets from B. thailandensis, and 25 orthologs from other Burkholderia species, yielding an overall structural coverage for 49 of the 406 essential gene families, with a total of 88 depositions into the Protein Data Bank. Of these, 25 proteins have properties of a potential antimicrobial drug target i.e., no close human homolog, part of an essential metabolic pathway, and a deep binding pocket. We describe the structures of several potential drug targets in detail. Conclusions/Significance This collection of structures, solubility and experimental essentiality data provides a resource for development of drugs against infections and diseases caused by Burkholderia. All expression clones and proteins created in this study are freely available by request. PMID:23382856

Structure-based discovery of selective serotonin 5-HT(1B) receptor ligands.

PubMed

Rodríguez, David; Brea, José; Loza, María Isabel; Carlsson, Jens

2014-08-05

The development of safe and effective drugs relies on the discovery of selective ligands. Serotonin (5-hydroxytryptamine [5-HT]) G protein-coupled receptors are therapeutic targets for CNS disorders but are also associated with adverse drug effects. The determination of crystal structures for the 5-HT1B and 5-HT2B receptors provided an opportunity to identify subtype selective ligands using structure-based methods. From docking screens of 1.3 million compounds, 22 molecules were predicted to be selective for the 5-HT1B receptor over the 5-HT2B subtype, a requirement for safe serotonergic drugs. Nine compounds were experimentally verified as 5-HT1B-selective ligands, with up to 300-fold higher affinities for this subtype. Three of the ligands were agonists of the G protein pathway. Analysis of state-of-the-art homology models of the two 5-HT receptors revealed that the crystal structures were critical for predicting selective ligands. Our results demonstrate that structure-based screening can guide the discovery of ligands with specific selectivity profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship.

PubMed

Huang, Xiao Yan; Shan, Zhi Jie; Zhai, Hong Lin; Li, Li Na; Zhang, Xiao Yun

2011-08-22

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.

Predicting drug side-effect profiles: a chemical fragment-based approach

PubMed Central

2011-01-01

Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

Pharmacogenomics of the human ABC transporter ABCG2: from functional evaluation to drug molecular design

NASA Astrophysics Data System (ADS)

Ishikawa, Toshihisa; Tamura, Ai; Saito, Hikaru; Wakabayashi, Kanako; Nakagawa, Hiroshi

2005-10-01

In the post-genome-sequencing era, emerging genomic technologies are shifting the paradigm for drug discovery and development. Nevertheless, drug discovery and development still remain high-risk and high-stakes ventures with long and costly timelines. Indeed, the attrition of drug candidates in preclinical and development stages is a major problem in drug design. For at least 30% of the candidates, this attrition is due to poor pharmacokinetics and toxicity. Thus, pharmaceutical companies have begun to seriously re-evaluate their current strategies of drug discovery and development. In that light, we propose that a transport mechanism-based design might help to create new, pharmacokinetically advantageous drugs, and as such should be considered an important component of drug design strategy. Performing enzyme- and/or cell-based drug transporter, interaction tests may greatly facilitate drug development and allow the prediction of drug-drug interactions. We recently developed methods for high-speed functional screening and quantitative structure-activity relationship analysis to study the substrate specificity of ABC transporters and to evaluate the effect of genetic polymorphisms on their function. These methods would provide a practical tool to screen synthetic and natural compounds, and these data can be applied to the molecular design of new drugs. In this review article, we present an overview on the genetic polymorphisms of human ABC transporter ABCG2 and new camptothecin analogues that can circumvent AGCG2-associated multidrug resistance of cancer.

Application of Various Types of Liposomes in Drug Delivery Systems

PubMed Central

Alavi, Mehran; Karimi, Naser; Safaei, Mohsen

2017-01-01

Liposomes, due to their various forms, require further exploration. These structures can deliver both hydrophilic and hydrophobic drugs for cancer, antibacterial, antifungal, immunomodulation, diagnostics, ophtalmica, vaccines, enzymes and genetic elements. Preparation of liposomes results in different properties for these systems. In addition, based on preparation methods, liposomes types can be unilamellar, multilamellar and giant unilamellar; however, there are many factors and difficulties that affect the development of liposome drug delivery structure. In the present review, we discuss some problems that impact drug delivery by liposomes. In addition, we discuss a new generation of liposomes, which is utilized for decreasing the limitation of the conventional liposomes. PMID:28507932

Structure and ligand-based design of P-glycoprotein inhibitors: a historical perspective.

PubMed

Palmeira, Andreia; Sousa, Emilia; Vasconcelos, M Helena; Pinto, Madalena; Fernandes, Miguel X

2012-01-01

Computer-assisted drug design (CADD) is a valuable approach for the discovery of new chemical entities in the field of cancer therapy. There is a pressing need to design and develop new, selective, and safe drugs for the treatment of multidrug resistance (MDR) cancer forms, specifically active against P-glycoprotein (P-gp). Recently, a crystallographic structure for mouse P-gp was obtained. However, for decades the design of new P-gp inhibitors employed mainly ligand-based approaches (SAR, QSAR, 3D-QSAR and pharmacophore studies), and structure-based studies used P-gp homology models. However, some of those results are still the pillars used as a starting point for the design of potential P-gp inhibitors. Here, pharmacophore mapping, (Q)SAR, 3D-QSAR and homology modeling, for the discovery of P-gp inhibitors are reviewed. The importance of these methods for understanding mechanisms of drug resistance at a molecular level, and design P-gp inhibitors drug candidates are discussed. The examples mentioned in the review could provide insights into the wide range of possibilities of using CADD methodologies for the discovery of efficient P-gp inhibitors.

A New Carbon Nanotube-Based Breast Cancer Drug Delivery System: Preparation and In Vitro Analysis Using Paclitaxel.

PubMed

Shao, Wei; Paul, Arghya; Rodes, Laetitia; Prakash, Satya

2015-04-01

Paclitaxel (PTX) is one of the most important drugs for breast cancer; however, the drug effects are limited by its systematic toxicity and poor water solubility. Nanoparticles have been applied for delivery of cancer drugs to overcome their limitations. Toward this goal, a novel single-walled carbon nanotube (SWNT)-based drug delivery system was developed by conjugation of human serum albumin (HSA) nanoparticles for loading of antitumor agent PTX. The nanosized macromolecular SWNT-drug carrier (SWNT-HSA) was characterized by TEM, UV-Vis-NIR spectrometry, and TGA. The SWNT-based drug carrier displayed high intracellular delivery efficiency (cell uptake rate of 80%) in breast cancer MCF-7 cells, as examined by fluorescence-labeled drug carriers, suggesting the needle-shaped SWNT-HSA drug carrier was able to transport drugs across cell membrane despite its macromolecular structure. The drug loading on SWNT-based drug carrier was through high binding affinity of PTX to HSA proteins. The PTX formulated with SWNT-HSA showed greater growth inhibition activity in MCF-7 breast cancer cells than PTX formulated with HSA nanoparticle only (cell viability of 63 vs 70% in 48 h and 53 vs 62% in 72 h). The increased drug efficacy could be driven by SWNT-mediated cell internalization. These data suggest that the developed SWNT-based antitumor agent is functional and effective. However, more studies for in vivo drug delivery efficacy and other properties are needed before this delivery system can be fully realized.

75 FR 52755 - Draft Guidance for Industry on Acute Bacterial Skin and Skin Structure Infections: Developing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-27

...] Draft Guidance for Industry on Acute Bacterial Skin and Skin Structure Infections: Developing Drugs for... ``Acute Bacterial Skin and Skin Structure Infections: Developing Drugs for Treatment.'' The purpose of... antimicrobial drugs for the treatment of acute bacterial skin and skin structure infections (ABSSSI), impetigo...

A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

PubMed

Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

Structure of the Trypanosoma cruzi protein tyrosine phosphatase TcPTP1, a potential therapeutic target for Chagas' disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lountos, George T.; Tropea, Joseph E.; Waugh, David S.

2013-06-05

Chagas’ disease, a neglected tropical affliction transmitted by the flagellated protozoan Trypanosoma cruzi, is prevalent in Latin America and affects nearly 18 million people worldwide, yet few approved drugs are available to treat the disease. Moreover, the currently available drugs exhibit severe toxicity or are poorly effective in the chronic phase of the disease. This limitation, along with the large population at risk, underscores the urgent need to discover new molecular targets and novel therapeutic agents. Recently, the T. cruzi protein tyrosine phosphatase TcPTP1 has been implicated in the cellular differentiation and infectivity of the parasite and is therefore amore » promising target for the design of novel anti-parasitic drugs. Here, we report the X-ray crystal structure of TcPTP1 refined to a resolution of 2.18 Å, which provides structural insights into the active site environment that can be used to initiate structure-based drug design efforts to develop specific TcPTP1 inhibitors. Potential strategies to develop such inhibitors are also discussed.« less

The Significance of G Protein-Coupled Receptor Crystallography for Drug Discovery

PubMed Central

Salon, John A.; Lodowski, David T.

2011-01-01

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

Crystal structure of Zika virus NS5 RNA-dependent RNA polymerase.

PubMed

Godoy, Andre S; Lima, Gustavo M A; Oliveira, Ketllyn I Z; Torres, Naiara U; Maluf, Fernando V; Guido, Rafael V C; Oliva, Glaucius

2017-03-27

The current Zika virus (ZIKV) outbreak became a global health threat of complex epidemiology and devastating neurological impacts, therefore requiring urgent efforts towards the development of novel efficacious and safe antiviral drugs. Due to its central role in RNA viral replication, the non-structural protein 5 (NS5) RNA-dependent RNA-polymerase (RdRp) is a prime target for drug discovery. Here we describe the crystal structure of the recombinant ZIKV NS5 RdRp domain at 1.9 Å resolution as a platform for structure-based drug design strategy. The overall structure is similar to other flaviviral homologues. However, the priming loop target site, which is suitable for non-nucleoside polymerase inhibitor design, shows significant differences in comparison with the dengue virus structures, including a tighter pocket and a modified local charge distribution.

Dynamic Structure-Based Pharmacophore Model Development: A New and Effective Addition in the Histone Deacetylase 8 (HDAC8) Inhibitor Discovery

PubMed Central

Thangapandian, Sundarapandian; John, Shalini; Lee, Yuno; Kim, Songmi; Lee, Keun Woo

2011-01-01

Histone deacetylase 8 (HDAC8) is an enzyme involved in deacetylating the amino groups of terminal lysine residues, thereby repressing the transcription of various genes including tumor suppressor gene. The over expression of HDAC8 was observed in many cancers and thus inhibition of this enzyme has emerged as an efficient cancer therapeutic strategy. In an effort to facilitate the future discovery of HDAC8 inhibitors, we developed two pharmacophore models containing six and five pharmacophoric features, respectively, using the representative structures from two molecular dynamic (MD) simulations performed in Gromacs 4.0.5 package. Various analyses of trajectories obtained from MD simulations have displayed the changes upon inhibitor binding. Thus utilization of the dynamically-responded protein structures in pharmacophore development has the added advantage of considering the conformational flexibility of protein. The MD trajectories were clustered based on single-linkage method and representative structures were taken to be used in the pharmacophore model development. Active site complimenting structure-based pharmacophore models were developed using Discovery Studio 2.5 program and validated using a dataset of known HDAC8 inhibitors. Virtual screening of chemical database coupled with drug-like filter has identified drug-like hit compounds that match the pharmacophore models. Molecular docking of these hits reduced the false positives and identified two potential compounds to be used in future HDAC8 inhibitor design. PMID:22272142

Modelling and enhanced molecular dynamics to steer structure-based drug discovery.

PubMed

Kalyaanamoorthy, Subha; Chen, Yi-Ping Phoebe

2014-05-01

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Characterizing protein domain associations by Small-molecule ligand binding

PubMed Central

Li, Qingliang; Cheng, Tiejun; Wang, Yanli; Bryant, Stephen H.

2012-01-01

Background Protein domains are evolutionarily conserved building blocks for protein structure and function, which are conventionally identified based on protein sequence or structure similarity. Small molecule binding domains are of great importance for the recognition of small molecules in biological systems and drug development. Many small molecules, including drugs, have been increasingly identified to bind to multiple targets, leading to promiscuous interactions with protein domains. Thus, a large scale characterization of the protein domains and their associations with respect to small-molecule binding is of particular interest to system biology research, drug target identification, as well as drug repurposing. Methods We compiled a collection of 13,822 physical interactions of small molecules and protein domains derived from the Protein Data Bank (PDB) structures. Based on the chemical similarity of these small molecules, we characterized pairwise associations of the protein domains and further investigated their global associations from a network point of view. Results We found that protein domains, despite lack of similarity in sequence and structure, were comprehensively associated through binding the same or similar small-molecule ligands. Moreover, we identified modules in the domain network that consisted of closely related protein domains by sharing similar biochemical mechanisms, being involved in relevant biological pathways, or being regulated by the same cognate cofactors. Conclusions A novel protein domain relationship was identified in the context of small-molecule binding, which is complementary to those identified by traditional sequence-based or structure-based approaches. The protein domain network constructed in the present study provides a novel perspective for chemogenomic study and network pharmacology, as well as target identification for drug repurposing. PMID:23745168

MSN anti-cancer nanomedicines: chemotherapy enhancement, overcoming of drug resistance, and metastasis inhibition.

PubMed

He, Qianjun; Shi, Jianlin

2014-01-22

In the anti-cancer war, there are three main obstacles resulting in high mortality and recurrence rate of cancers: the severe toxic side effect of anti-cancer drugs to normal tissues due to the lack of tumor-selectivity, the multi-drug resistance (MDR) to free chemotherapeutic drugs and the deadly metastases of cancer cells. The development of state-of-art nanomedicines based on mesoporous silica nanoparticles (MSNs) is expected to overcome the above three main obstacles. In the view of the fast development of anti-cancer strategy, this review highlights the most recent advances of MSN anti-cancer nanomedicines in enhancing chemotherapeutic efficacy, overcoming the MDR and inhibiting metastasis. Furthermore, we give an outlook of the future development of MSNs-based anti-cancer nanomedicines, and propose several innovative and forward-looking anti-cancer strategies, including tumor tissue-cell-nuclear successionally targeted drug delivery strategy, tumor cell-selective nuclear-targeted drug delivery strategy, multi-targeting and multi-drug strategy, chemo-/radio-/photodynamic-/ultrasound-/thermo-combined multi-modal therapy by virtue of functionalized hollow/rattle-structured MSNs. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Structural View on Medicinal Chemistry Strategies against Drug Resistance.

PubMed

Agnello, Stefano; Brand, Michael; Chellat, Mathieu F; Gazzola, Silvia; Riedl, Rainer

2018-05-30

The natural phenomenon of drug resistance represents a generic impairment that hampers the benefits of drugs in all major clinical indications. Antibacterials and antifungals are affected as well as compounds for the treatment of cancer, viral infections or parasitic diseases. Despite the very diverse set of biological targets and organisms involved in the development of drug resistance, underlying molecular processes have been identified to understand the emergence of resistance and to overcome this detrimental mechanism. Detailed structural information of the root causes for drug resistance is nowadays frequently available to design next generation drugs anticipated to suffer less from resistance. This knowledge-based approach is a prerequisite in the fight against the inevitable occurrence of drug resistance to secure the achievements of medicinal chemistry in the future. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking

PubMed Central

Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

2013-01-01

Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional) structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called “iGPCR-drug”, was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional) fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition) generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug – target interaction networks. PMID:24015221

MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development

PubMed Central

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/. PMID:25928885

Permeation enhancer strategies in transdermal drug delivery.

PubMed

Marwah, Harneet; Garg, Tarun; Goyal, Amit K; Rath, Goutam

2016-01-01

Today, ∼74% of drugs are taken orally and are not found to be as effective as desired. To improve such characteristics, transdermal drug delivery was brought to existence. This delivery system is capable of transporting the drug or macromolecules painlessly through skin into the blood circulation at fixed rate. Topical administration of therapeutic agents offers many advantages over conventional oral and invasive techniques of drug delivery. Several important advantages of transdermal drug delivery are prevention from hepatic first pass metabolism, enhancement of therapeutic efficiency and maintenance of steady plasma level of the drug. Human skin surface, as a site of drug application for both local and systemic effects, is the most eligible candidate available. New controlled transdermal drug delivery systems (TDDS) technologies (electrically-based, structure-based and velocity-based) have been developed and commercialized for the transdermal delivery of troublesome drugs. This review article covers most of the new active transport technologies involved in enhancing the transdermal permeation via effective drug delivery system.

iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking

PubMed Central

Min, Jian-Liang; Chou, Kuo-Chen

2013-01-01

With the features of extremely high selectivity and efficiency in catalyzing almost all the chemical reactions in cells, enzymes play vitally important roles for the life of an organism and hence have become frequent targets for drug design. An essential step in developing drugs by targeting enzymes is to identify drug-enzyme interactions in cells. It is both time-consuming and costly to do this purely by means of experimental techniques alone. Although some computational methods were developed in this regard based on the knowledge of the three-dimensional structure of enzyme, unfortunately their usage is quite limited because three-dimensional structures of many enzymes are still unknown. Here, we reported a sequence-based predictor, called “iEzy-Drug,” in which each drug compound was formulated by a molecular fingerprint with 258 feature components, each enzyme by the Chou's pseudo amino acid composition generated via incorporating sequential evolution information and physicochemical features derived from its sequence, and the prediction engine was operated by the fuzzy K-nearest neighbor algorithm. The overall success rate achieved by iEzy-Drug via rigorous cross-validations was about 91%. Moreover, to maximize the convenience for the majority of experimental scientists, a user-friendly web server was established, by which users can easily obtain their desired results. PMID:24371828

Beyond small molecule SAR – using the dopamine D3 receptor crystal structure to guide drug design

PubMed Central

Keck, Thomas M.; Burzynski, Caitlin; Shi, Lei; Newman, Amy Hauck

2016-01-01

The dopamine D3 receptor is a target of pharmacotherapeutic interest in a variety of neurological disorders including schizophrenia, restless leg syndrome, and drug addiction. The high protein sequence homology between the D3 and D2 receptors has posed a challenge to developing D3 receptor-selective ligands whose behavioral actions can be attributed to D3 receptor engagement, in vivo. However, through primarily small molecule structure-activity relationship (SAR) studies, a variety of chemical scaffolds have been discovered over the past two decades that have resulted in several D3 receptor-selective ligands with high affinity and in vivo activity. Nevertheless, viable clinical candidates remain limited. The recent determination of the high-resolution crystal structure of the D3 receptor has invigorated structure-based drug design, providing refinements to the molecular dynamic models and testable predictions about receptor-ligand interactions. This review will highlight recent preclinical and clinical studies demonstrating potential utility of D3 receptor-selective ligands in the treatment of addiction. In addition, new structure-based rational drug design strategies for D3 receptor-selective ligands that complement traditional small molecule SAR to improve the selectivity and directed efficacy profiles are examined. PMID:24484980

Dendrimers in Medicine: Therapeutic Concepts and Pharmaceutical Challenges.

PubMed

Wu, Lin-Ping; Ficker, Mario; Christensen, Jørn B; Trohopoulos, Panagiotis N; Moghimi, Seyed Moein

2015-07-15

Dendrimers are three-dimensional macromolecular structures originating from a central core molecule and surrounded by successive addition of branching layers (generation). These structures exhibit a high degree of molecular uniformity, narrow molecular weight distribution, tunable size and shape characteristics, as well as multivalency. Collectively, these physicochemical characteristics together with advancements in design of biodegradable backbones have conferred many applications to dendrimers in formulation science and nanopharmaceutical developments. These have included the use of dendrimers as pro-drugs and vehicles for solubilization, encapsulation, complexation, delivery, and site-specific targeting of small-molecule drugs, biopharmaceuticals, and contrast agents. We briefly review these advances, paying particular attention to attributes that make dendrimers versatile for drug formulation as well as challenging issues surrounding the future development of dendrimer-based medicines.

Cyclodextrin based nanosponges for pharmaceutical use: a review.

PubMed

Tejashri, Gursalkar; Amrita, Bajaj; Darshana, Jain

2013-09-01

Nanosponges are a novel class of hyper-crosslinked polymer based colloidal structures consisting of solid nanoparticles with colloidal sizes and nanosized cavities. These nano-sized colloidal carriers have been recently developed and proposed for drug delivery, since their use can solubilize poorly water-soluble drugs and provide prolonged release as well as improve a drug's bioavailability by modifying the pharmacokinetic parameters of actives. Development of nanosponges as drug delivery systems, with special reference to cyclodextrin based nanosponges, is presented in this article. In the current review, attempts have been made to illustrate the features of cyclodextrin based nanosponges and their applications in pharmaceutical formulations. Special emphasis has been placed on discussing the methods of preparation, characterization techniques and applications of these novel drug delivery carriers for therapeutic purposes. Nanosponges can be referred to as solid porous particles having a capacity to load drugs and other actives into their nanocavity; they can be formulated as oral, parenteral, topical or inhalation dosage forms. Nanosponges offer high drug loading compared to other nanocarriers and are thus suitable for solving issues related to stability, solubility and delayed release of actives. Controlled release of the loaded actives and solubility enhancement of poorly water-soluble drugs are major advantages of nanosponge drug delivery systems.

Cheminformatic comparison of approved drugs from natural product versus synthetic origins.

PubMed

Stratton, Christopher F; Newman, David J; Tan, Derek S

2015-11-01

Despite the recent decline of natural product discovery programs in the pharmaceutical industry, approximately half of all new drug approvals still trace their structural origins to a natural product. Herein, we use principal component analysis to compare the structural and physicochemical features of drugs from natural product-based versus completely synthetic origins that were approved between 1981 and 2010. Drugs based on natural product structures display greater chemical diversity and occupy larger regions of chemical space than drugs from completely synthetic origins. Notably, synthetic drugs based on natural product pharmacophores also exhibit lower hydrophobicity and greater stereochemical content than drugs from completely synthetic origins. These results illustrate that structural features found in natural products can be successfully incorporated into synthetic drugs, thereby increasing the chemical diversity available for small-molecule drug discovery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational challenges of structure-based approaches applied to HIV.

PubMed

Forli, Stefano; Olson, Arthur J

2015-01-01

Here, we review some of the opportunities and challenges that we face in computational modeling of HIV therapeutic targets and structural biology, both in terms of methodology development and structure-based drug design (SBDD). Computational methods have provided fundamental support to HIV research since the initial structural studies, helping to unravel details of HIV biology. Computational models have proved to be a powerful tool to analyze and understand the impact of mutations and to overcome their structural and functional influence in drug resistance. With the availability of structural data, in silico experiments have been instrumental in exploiting and improving interactions between drugs and viral targets, such as HIV protease, reverse transcriptase, and integrase. Issues such as viral target dynamics and mutational variability, as well as the role of water and estimates of binding free energy in characterizing ligand interactions, are areas of active computational research. Ever-increasing computational resources and theoretical and algorithmic advances have played a significant role in progress to date, and we envision a continually expanding role for computational methods in our understanding of HIV biology and SBDD in the future.

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

Drug search for leishmaniasis: a virtual screening approach by grid computing

NASA Astrophysics Data System (ADS)

Ochoa, Rodrigo; Watowich, Stanley J.; Flórez, Andrés; Mesa, Carol V.; Robledo, Sara M.; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in 100 countries, with infections causing 2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen 2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Drug search for leishmaniasis: a virtual screening approach by grid computing.

PubMed

Ochoa, Rodrigo; Watowich, Stanley J; Flórez, Andrés; Mesa, Carol V; Robledo, Sara M; Muskus, Carlos

2016-07-01

The trypanosomatid protozoa Leishmania is endemic in ~100 countries, with infections causing ~2 million new cases of leishmaniasis annually. Disease symptoms can include severe skin and mucosal ulcers, fever, anemia, splenomegaly, and death. Unfortunately, therapeutics approved to treat leishmaniasis are associated with potentially severe side effects, including death. Furthermore, drug-resistant Leishmania parasites have developed in most endemic countries. To address an urgent need for new, safe and inexpensive anti-leishmanial drugs, we utilized the IBM World Community Grid to complete computer-based drug discovery screens (Drug Search for Leishmaniasis) using unique leishmanial proteins and a database of 600,000 drug-like small molecules. Protein structures from different Leishmania species were selected for molecular dynamics (MD) simulations, and a series of conformational "snapshots" were chosen from each MD trajectory to simulate the protein's flexibility. A Relaxed Complex Scheme methodology was used to screen ~2000 MD conformations against the small molecule database, producing >1 billion protein-ligand structures. For each protein target, a binding spectrum was calculated to identify compounds predicted to bind with highest average affinity to all protein conformations. Significantly, four different Leishmania protein targets were predicted to strongly bind small molecules, with the strongest binding interactions predicted to occur for dihydroorotate dehydrogenase (LmDHODH; PDB:3MJY). A number of predicted tight-binding LmDHODH inhibitors were tested in vitro and potent selective inhibitors of Leishmania panamensis were identified. These promising small molecules are suitable for further development using iterative structure-based optimization and in vitro/in vivo validation assays.

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs

PubMed Central

2016-01-01

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

Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.

PubMed

Wagner, Jeffrey R; Lee, Christopher T; Durrant, Jacob D; Malmstrom, Robert D; Feher, Victoria A; Amaro, Rommie E

2016-06-08

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.

Insights from investigating the interactions of adamantane-based drugs with the M2 proton channel from the H1N1 swine virus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing-Fang; Wei, Dong-Qing, E-mail: dqwei@gordonlifescience.org; Gordon Life Science Institute, 13784 Torrey Del Mar Drive, San Diego, CA 92130

The M2 proton channel is one of indispensable components for the influenza A virus that plays a vital role in its life cycle and hence is an important target for drug design against the virus. In view of this, the three-dimensional structure of the H1N1-M2 channel was developed based on the primary sequence taken from a patient recently infected by the H1N1 (swine flu) virus. With an explicit water-membrane environment, molecular docking studies were performed for amantadine and rimantadine, the two commercial drugs generally used to treat influenza A infection. It was found that their binding affinity to the H1N1-M2more » channel is significantly lower than that to the H5N1-M2 channel, fully consistent with the recent report that the H1N1 swine virus was resistant to the two drugs. The findings and the relevant analysis reported here might provide useful structural insights for developing effective drugs against the new swine flu virus.« less

Adamantane in Drug Delivery Systems and Surface Recognition.

PubMed

Štimac, Adela; Šekutor, Marina; Mlinarić-Majerski, Kata; Frkanec, Leo; Frkanec, Ruža

2017-02-16

The adamantane moiety is widely applied in design and synthesis of new drug delivery systems and in surface recognition studies. This review focuses on liposomes, cyclodextrins, and dendrimers based on or incorporating adamantane derivatives. Our recent concept of adamantane as an anchor in the lipid bilayer of liposomes has promising applications in the field of targeted drug delivery and surface recognition. The results reported here encourage the development of novel adamantane-based structures and self-assembled supramolecular systems for basic chemical investigations as well as for biomedical application.

A structure- and chemical genomics-based approach for repositioning of drugs against VCP/p97 ATPase.

PubMed

Segura-Cabrera, Aldo; Tripathi, Reshmi; Zhang, Xiaoyi; Gui, Lin; Chou, Tsui-Fen; Komurov, Kakajan

2017-03-21

Valosin-containing protein (VCP/p97) ATPase (a.k.a. Cdc48) is a key member of the ER-associated protein degradation (ERAD) pathway. ERAD and VCP/p97 have been implicated in a multitude of human diseases, such as neurodegenerative diseases and cancer. Inhibition of VCP/p97 induces proteotoxic ER stress and cell death in cancer cells, making it an attractive target for cancer treatment. However, no drugs exist against this protein in the market. Repositioning of drugs towards new indications is an attractive alternative to the de novo drug development due to the potential for significantly shorter time to clinical translation. Here, we employed an integrative strategy for the repositioning of drugs as novel inhibitors of the VCP/p97 ATPase. We integrated structure-based virtual screening with the chemical genomics analysis of drug molecular signatures, and identified several candidate inhibitors of VCP/p97 ATPase. Importantly, experimental validation with cell-based and in vitro ATPase assays confirmed three (ebastine, astemizole and clotrimazole) out of seven tested candidates (~40% true hit rate) as direct inhibitors of VCP/p97 and ERAD. This study introduces an effective integrative strategy for drug repositioning, and identified new drugs against the VCP/p97/ERAD pathway in human diseases.

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities.

PubMed

Huang, Boshi; Kang, Dongwei; Zhan, Peng; Liu, Xinyong

2015-12-01

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery. In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress. Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods.

PubMed

Moitessier, Nicolas; Pottel, Joshua; Therrien, Eric; Englebienne, Pablo; Liu, Zhaomin; Tomberg, Anna; Corbeil, Christopher R

2016-09-20

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.

Specialty pharmaceuticals: policy initiatives to improve assessment, pricing, prescription, and use.

PubMed

Robinson, James C; Howell, Scott

2014-10-01

The value of "specialty pharmaceuticals" for cancer and other complex conditions depends not merely on their molecular structures but also on the manner in which the drugs are assessed, insured, priced, prescribed, and used. This article analyzes the five principal stages through which a specialty drug must pass on its journey from the laboratory to the bedside. These include regulatory approval by the Food and Drug Administration for market access, insurance coverage, pricing and payment, physician prescription, and patient engagement. If structured appropriately, each stage improves performance and supports continued research and development. If structured inappropriately, however, each stage adds to administrative burdens, distorts clinical decision making, and weakens incentives for innovation. Cautious optimism is in order, but neither the continued development of breakthrough products nor their use according to evidence-based guidelines can be taken for granted. Project HOPE—The People-to-People Health Foundation, Inc.

Application of ethyl cellulose, microcrystalline cellulose and octadecanol for wax based floating solid dispersion pellets.

PubMed

Yan, Hong-Xiang; Zhang, Shuang-Shuang; He, Jian-Hua; Liu, Jian-Ping

2016-09-05

The present study aimed to develop and optimize the wax based floating sustained-release dispersion pellets for a weakly acidic hydrophilic drug protocatechuic acid to achieve prolonged gastric residence time and improved bioavailability. This low-density drug delivery system consisted of octadecanol/microcrystalline cellulose mixture matrix pellet cores prepared by extrusion-spheronization technique, coated with drug/ethyl cellulose 100cp solid dispersion using single-step fluid-bed coating method. The formulation-optimized pellets could maintain excellent floating state without lag time and sustain the drug release efficiently for 12h based on non-Fickian transport mechanism. Observed by SEM, the optimized pellet was the dispersion-layered spherical structure containing a compact inner core. DSC, XRD and FTIR analysis revealed drug was uniformly dispersed in the amorphous molecule form and had no significant physicochemical interactions with the polymer dispersion carrier. The stability study of the resultant pellets further proved the rationality and integrity of the developed formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolic cancer biology: structural-based analysis of cancer as a metabolic disease, new sights and opportunities for disease treatment.

PubMed

Masoudi-Nejad, Ali; Asgari, Yazdan

2015-02-01

The cancer cell metabolism or the Warburg effect discovery goes back to 1924 when, for the first time Otto Warburg observed, in contrast to the normal cells, cancer cells have different metabolism. With the initiation of high throughput technologies and computational systems biology, cancer cell metabolism renaissances and many attempts were performed to revise the Warburg effect. The development of experimental and analytical tools which generate high-throughput biological data including lots of information could lead to application of computational models in biological discovery and clinical medicine especially for cancer. Due to the recent availability of tissue-specific reconstructed models, new opportunities in studying metabolic alteration in various kinds of cancers open up. Structural approaches at genome-scale levels seem to be suitable for developing diagnostic and prognostic molecular signatures, as well as in identifying new drug targets. In this review, we have considered these recent advances in structural-based analysis of cancer as a metabolic disease view. Two different structural approaches have been described here: topological and constraint-based methods. The ultimate goal of this type of systems analysis is not only the discovery of novel drug targets but also the development of new systems-based therapy strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Gyanendra; Swaminathan, Subramanyam

Botulinum Neurotoxins are the most poisonous of all toxins with lethal dose in nanogram quantities. They are also potential biological warfare and bioterrorism agents due to their high toxicity and ease of preparation. On the other hand BoNTs are also being increasingly used for therapeutic and cosmetic purposes, and with that the chances of accidental overdose are increasing. And despite the potential damage they could cause to human health, there are no post-intoxication drugs available so far. But progress is being made in this direction. The crystal structures in native form and bound with substrate peptides have been determined, andmore » these are enabling structure-based drug discovery possible. High throughput assays have also been designed to speed up the screening progress. Substrate-based and small molecule inhibitors have been identified. But turning high affinity inhibitors into clinically viable drug candidates has remained a challenge. We discuss here the latest developments and the future challenges in drug discovery for Botulinum neurotoxins.« less

[A novel dipeptidyl peptidase IV inhibitors developed through scaffold hopping and drug splicing strategy].

PubMed

Wang, Shan-Chun; Zeng, Li-Li; Ding, Yu-Yang; Zeng, Shao-Gao; Song, Hong-Rui; Hu, Wen-Hui; Xie, Hui

2014-01-01

Though all the marketed drugs of dipeptidyl peptidase IV inhibitors are structurally different, their inherent correlation is worthy of further investigation. Herein we rapidly discovered a novel DPP-IV inhibitor 8g (IC50 = 4.9 nmol.L-1) which exhibits as good activity and selectivity as the market drugs through scaffold hopping and drug splicing strategies based on alogliptin and linagliptin. This study demonstrated that the employment of classic medicinal chemistry strategy to the marketed drugs with specific target is an efficient approach to discover novel bioactive molecules.

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

NASA Astrophysics Data System (ADS)

Baumgartner, Matthew P.; Evans, David A.

2018-01-01

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ = 0.614), performed slightly better than our ligand-based methods (ρ = 0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.

Preclinical drug development.

PubMed

Brodniewicz, Teresa; Grynkiewicz, Grzegorz

2010-01-01

Life sciences provide reasonably sound prognosis for a number and nature of therapeutic targets on which drug design could be based, and search for new chemical entities--future new drugs, is now more than ever based on scientific principles. Nevertheless, current very long and incredibly costly drug discovery and development process is very inefficient, with attrition rate spanning from many thousands of new chemical structures, through a handful of validated drug leads, to single successful new drug launches, achieved in average after 13 years, with compounded cost estimates from hundreds of thousands to over one billion US dollars. Since radical pharmaceutical innovation is critically needed, number of new research projects concerning this area is steeply rising outside of big pharma industry--both in academic environment and in small private companies. Their prospective success will critically depend on project management, which requires combined knowledge of scientific, technical and legal matters, comprising regulations concerning admission of new drug candidates to be subjects of clinical studies. This paper attempts to explain basic rules and requirements of drug development within preclinical study period, in case of new chemical entities of natural or synthetic origin, which belong to low molecular weight category.

Novel Non-Peptide Inhibitors against SmCL1 of Schistosoma mansoni: In Silico Elucidation, Implications and Evaluation via Knowledge Based Drug Discovery

PubMed Central

Zafar, Atif; Ahmad, Sabahuddin; Rizvi, Asim; Ahmad, Masood

2015-01-01

Schistosomiasis is a major endemic disease known for excessive mortality and morbidity in developing countries. Because praziquantel is the only drug available for its treatment, the risk of drug resistance emphasizes the need to discover new drugs for this disease. Cathepsin SmCL1 is the critical target for drug design due to its essential role in the digestion of host proteins for growth and development of Schistosoma mansoni. Inhibiting the function of SmCL1 could control the wide spread of infections caused by S. mansoni in humans. With this objective, a homology modeling approach was used to obtain theoretical three-dimensional (3D) structure of SmCL1. In order to find the potential inhibitors of SmCL1, a plethora of in silico techniques were employed to screen non-peptide inhibitors against SmCL1 via structure-based drug discovery protocol. Receiver operating characteristic (ROC) curve analysis and molecular dynamics (MD) simulation were performed on the results of docked protein-ligand complexes to identify top ranking molecules against the modelled 3D structure of SmCL1. MD simulation results suggest the phytochemical Simalikalactone-D as a potential lead against SmCL1, whose pharmacophore model may be useful for future screening of potential drug molecules. To conclude, this is the first report to discuss the virtual screening of non-peptide inhibitors against SmCL1 of S. mansoni, with significant therapeutic potential. Results presented herein provide a valuable contribution to identify the significant leads and further derivatize them to suitable drug candidates for antischistosomal therapy. PMID:25933436

Combining NMR and X-ray crystallography in fragment-based drug discovery: discovery of highly potent and selective BACE-1 inhibitors.

PubMed

Wyss, Daniel F; Wang, Yu-Sen; Eaton, Hugh L; Strickland, Corey; Voigt, Johannes H; Zhu, Zhaoning; Stamford, Andrew W

2012-01-01

Fragment-based drug discovery (FBDD) has become increasingly popular over the last decade. We review here how we have used highly structure-driven fragment-based approaches to complement more traditional lead discovery to tackle high priority targets and those struggling for leads. Combining biomolecular nuclear magnetic resonance (NMR), X-ray crystallography, and molecular modeling with structure-assisted chemistry and innovative biology as an integrated approach for FBDD can solve very difficult problems, as illustrated in this chapter. Here, a successful FBDD campaign is described that has allowed the development of a clinical candidate for BACE-1, a challenging CNS drug target. Crucial to this achievement were the initial identification of a ligand-efficient isothiourea fragment through target-based NMR screening and the determination of its X-ray crystal structure in complex with BACE-1, which revealed an extensive H-bond network with the two active site aspartate residues. This detailed 3D structural information then enabled the design and validation of novel, chemically stable and accessible heterocyclic acylguanidines as aspartic acid protease inhibitor cores. Structure-assisted fragment hit-to-lead optimization yielded iminoheterocyclic BACE-1 inhibitors that possess desirable molecular properties as potential therapeutic agents to test the amyloid hypothesis of Alzheimer's disease in a clinical setting.

A Rapid Python-Based Methodology for Target-Focused Combinatorial Library Design.

PubMed

Li, Shiliang; Song, Yuwei; Liu, Xiaofeng; Li, Honglin

2016-01-01

The chemical space is so vast that only a small portion of it has been examined. As a complementary approach to systematically probe the chemical space, virtual combinatorial library design has extended enormous impacts on generating novel and diverse structures for drug discovery. Despite the favorable contributions, high attrition rates in drug development that mainly resulted from lack of efficacy and side effects make it increasingly challenging to discover good chemical starting points. In most cases, focused libraries, which are restricted to particular regions of the chemical space, are deftly exploited to maximize hit rate and improve efficiency at the beginning of the drug discovery and drug development pipeline. This paper presented a valid methodology for fast target-focused combinatorial library design in both reaction-based and production-based ways with the library creating rates of approximately 70,000 molecules per second. Simple, quick and convenient operating procedures are the specific features of the method. SHAFTS, a hybrid 3D similarity calculation software, was embedded to help refine the size of the libraries and improve hit rates. Two target-focused (p38-focused and COX2-focused) libraries were constructed efficiently in this study. This rapid library enumeration method is portable and applicable to any other targets for good chemical starting points identification collaborated with either structure-based or ligand-based virtual screening.

Using X-Ray Crystallography to Simplify and Accelerate Biologics Drug Development.

PubMed

Brader, Mark L; Baker, Edward N; Dunn, Michael F; Laue, Thomas M; Carpenter, John F

2017-02-01

Every major biopharmaceutical company incorporates a protein crystallography unit that is central to its structure-based drug discovery efforts. Yet these capabilities are rarely leveraged toward the formal higher order structural characterization that is so challenging but integral to large-scale biologics manufacturing. Although the biotech industry laments the shortcomings of its favored biophysical techniques, x-ray crystallography is not even considered for drug development. Why not? We suggest that this is due, at least in part, to outdated thinking (for a recent industry-wide survey, see Gabrielson JP, Weiss IV WF. Technical decision-making with higher order structure data: starting a new dialogue. J Pharm Sci. 2015;104(4):1240-1245). We examine some myths surrounding protein crystallography and highlight the inherent properties of protein crystals (molecular identity, biochemical purity, conformational uniformity, and macromolecular crowding) as having practicable commonalities with today's patient-focused liquid drug products. In the new millennium, protein crystallography has become essentially a routine analytical test. Its application may aid the identification of better candidate molecules that are more amenable to high-concentration processing, formulation, and analysis thereby helping to make biologics drug development quicker, simpler, and cheaper. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data

PubMed Central

Wang, Yongcui; Chen, Shilong; Deng, Naiyang; Wang, Yong

2013-01-01

Computational inference of novel therapeutic values for existing drugs, i.e., drug repositioning, offers the great prospect for faster and low-risk drug development. Previous researches have indicated that chemical structures, target proteins, and side-effects could provide rich information in drug similarity assessment and further disease similarity. However, each single data source is important in its own way and data integration holds the great promise to reposition drug more accurately. Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases. Then we train a support vector machine (SVM) to computationally predict novel drug-disease interactions. PreDR is validated on a well-established drug-disease network with 1,933 interactions among 593 drugs and 313 diseases. By cross-validation, we find that chemical structure, drug target, and side-effects information are all predictive for drug-disease relationships. More experimentally observed drug-disease interactions can be revealed by integrating these three data sources. Comparison with existing methods demonstrates that PreDR is competitive both in accuracy and coverage. Follow-up database search and pathway analysis indicate that our new predictions are worthy of further experimental validation. Particularly several novel predictions are supported by clinical trials databases and this shows the significant prospects of PreDR in future drug treatment. In conclusion, our new method, PreDR, can serve as a useful tool in drug discovery to efficiently identify novel drug-disease interactions. In addition, our heterogeneous data integration framework can be applied to other problems. PMID:24244318

Nanocrystal for ocular drug delivery: hope or hype.

PubMed

Sharma, Om Prakash; Patel, Viral; Mehta, Tejal

2016-08-01

The complexity of the structure and nature of the eye emanates a challenge for drug delivery to formulation scientists. Lower bioavailability concern of conventional ocular formulation provokes the interest of researchers in the development of novel drug delivery system. Nanotechnology-based formulations have been extensively investigated and found propitious in improving bioavailability of drugs by overcoming ocular barriers prevailing in the eye. The advent of nanocrystals helped in combating the problem of poorly soluble drugs specifically for oral and parenteral drug delivery and led to development of various marketed products. Nanocrystal-based formulations explored for ocular drug delivery have been found successful in achieving increase in retention time, bioavailability, and permeability of drugs across the corneal and conjunctival epithelium. In this review, we have highlighted the ocular physiology and barriers in drug delivery. A comparative analysis of various nanotechnology-based ocular formulations is done with their pros and cons. Consideration is also given to various methods of preparation of nanocrystals with their patented technology. This article highlights the success achieved in conquering various challenges of ocular delivery by the use of nanocrystals while emphasizing on its advantages and application for ocular formulation. The perspectives of nanocrystals as an emerging flipside to explore the frontiers of ocular drug delivery are discussed.

78 FR 63220 - Guidance for Industry on Acute Bacterial Skin and Skin Structure Infections: Developing Drugs for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

...] Guidance for Industry on Acute Bacterial Skin and Skin Structure Infections: Developing Drugs for Treatment... Administration (FDA) is announcing the availability of a guidance for industry entitled ``Acute Bacterial Skin and Skin Structure Infections: Developing Drugs for Treatment.'' The purpose of this guidance is to...

Biomimetic Solid Lipid Nanoparticles of Sophorolipids Designed for Antileprosy Drugs.

PubMed

Kanwar, Rohini; Gradzielski, Michael; Mehta, S K

2018-06-22

The objective of the present work was to develop solid lipid nanoparticles (SLNs) as drug-encapsulating structures by the solvent injection method. In this report, for the first time the inherent potential of lactonic sophorolipid (glycolipid) was exploited to formulate SLNs. A range of different Pluronic copolymers were screened by dynamic and static light scattering with the aim of obtaining most stable SLNs. To comprehend the structure of the SLNs, techniques such as transmission electron microscopy, differential scanning calorimetry, Fourier transform infrared spectroscopy, and X-ray diffraction were employed. A clear correlation between the type of Pluronic and size and stability of the SLNs could be drawn. The vector properties of the formed SLNs were assessed for both the encapsulated hydrophobic drugs-rifampicin and dapsone. To elucidate the transport mechanism of drug release, kinetic modeling was carried out on the drug release profiles. The promising results of sophorolipid-based SLNs have actually established a new arena beneath the significantly developed field of SLNs.

DNA-PKcs, a novel functional target of acriflavine, mediates acriflavine's p53-dependent synergistic anti-tumor efficiency with melphalan.

PubMed

Cao, Ji; Lin, Guanyu; Gong, Yanling; Pan, Peichen; Ma, Yaxi; Huang, Ping; Ying, Meidan; Hou, Tingjun; He, Qiaojun; Yang, Bo

2016-12-01

Acriflavine (ACF), a known antibacterial drug, has recently been recognized as a suitable candidate for cancer chemotherapy. However, the molecular target of ACF is not fully understood, which limits its application in cancer therapy. In this study, we established a structure-specific probe-based pull-down approach to comprehensively profile the potential target of ACF, and we identified DNA dependent protein kinase catalytic subunit (DNA-PKcs) as the direct target of ACF. Since DNA-PKcs facilitates the repair process following DNA double-strand breaks, we further developed a drug combination strategy that combined ACF with the bifunctional alkylating agent melphalan, which exerted a p53-dependent synergistic efficacy against human cancer cells both in vitro and in vivo. With these findings, our study demonstrated that structure-specific probe-based pull-down approaches can be used to identify new functional target of drug, and provided novel opportunities for the development of ACF-based antitumor chemotherapies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Comparative protein modeling of methionine S-adenosyltransferase (MAT) enzyme from Mycobacterium tuberculosis: a potential target for antituberculosis drug discovery.

PubMed

Khedkar, Santosh A; Malde, Alpeshkumar K; Coutinho, Evans C

2005-01-01

Mycobacterium tuberculosis (Mtb) is a successful pathogen that overcomes the numerous challenges presented by the immune system of the host. In the last 40 years few anti-TB drugs have been developed, while the drug-resistance problem is increasing; there is thus a pressing need to develop new anti-TB drugs active against both the acute and chronic growth phases of the mycobacterium. Methionine S-adenosyltransferase (MAT) is an enzyme involved in the synthesis of S-adenosylmethionine (SAM), a methyl donor essential for mycolipid biosynthesis. As an anti-TB drug target, Mtb-MAT has been well validated. A homology model of MAT has been constructed using the X-ray structures of E. coli MAT (PDB code: 1MXA) and rat MAT (PDB code: 1QM4) as templates, by comparative protein modeling principles. The resulting model has the correct stereochemistry as gauged from the Ramachandran plot and good three-dimensional (3D) structure compatibility as assessed by the Profiles-3D score. The structurally and functionally important residues (active site) of Mtb-MAT have been identified using the E. coli and rat MAT crystal structures and the reported point mutation data. The homology model conserves the topological and active site features of the MAT family of proteins. The differences in the molecular electrostatic potentials (MEP) of Mtb and human MAT provide evidences that selective and specific Mtb-MAT inhibitors can be designed using the homology model, by the structure-based drug design approaches.

CancerDR: cancer drug resistance database.

PubMed

Kumar, Rahul; Chaudhary, Kumardeep; Gupta, Sudheer; Singh, Harinder; Kumar, Shailesh; Gautam, Ankur; Kapoor, Pallavi; Raghava, Gajendra P S

2013-01-01

Cancer therapies are limited by the development of drug resistance, and mutations in drug targets is one of the main reasons for developing acquired resistance. The adequate knowledge of these mutations in drug targets would help to design effective personalized therapies. Keeping this in mind, we have developed a database "CancerDR", which provides information of 148 anti-cancer drugs, and their pharmacological profiling across 952 cancer cell lines. CancerDR provides comprehensive information about each drug target that includes; (i) sequence of natural variants, (ii) mutations, (iii) tertiary structure, and (iv) alignment profile of mutants/variants. A number of web-based tools have been integrated in CancerDR. This database will be very useful for identification of genetic alterations in genes encoding drug targets, and in turn the residues responsible for drug resistance. CancerDR allows user to identify promiscuous drug molecules that can kill wide range of cancer cells. CancerDR is freely accessible at http://crdd.osdd.net/raghava/cancerdr/

The patents-based pharmaceutical development process: rationale, problems, and potential reforms.

PubMed

Barton, John H; Emanuel, Ezekiel J

2005-10-26

The pharmaceutical industry is facing substantial criticism from many directions, including financial barriers to access to drugs in both developed and developing countries, high profits, spending on advertising and marketing, and other issues. Underlying these criticisms are fundamental questions about the value of the current patent-based drug development system. Six major problems with the patent system are (1) recovery of research costs by patent monopoly reduces access to drugs; (2) market demand rather than health needs determines research priorities; (3) resources between research and marketing are misallocated; (4) the market for drugs has inherent market failures; (5) overall investment in drug research and development is too low, compared with profits; and (6) the existing system discriminates against US patients. Potential solutions fall into 3 categories: change in drug pricing through either price controls or tiered pricing; change in drug industry structure through a "buy-out" pricing system or with the public sector acting as exclusive research funder; and change in development incentives through a disease burden incentive system, orphan drug approaches, or requiring new drugs to demonstrate improvement over existing products prior to US Food and Drug Administration approval. We recommend 4 complementary reforms: (1) having no requirement to test new drug products against existing products prior to approval but requiring rigorous comparative postapproval testing; (2) international tiered pricing and systematic safeguards to prevent flow-back; (3) increased government-funded research and buy-out for select conditions; and (4) targeted experiments using other approaches for health conditions in which there has been little progress and innovation over the last few decades.

StraPep: a structure database of bioactive peptides

PubMed Central

Wang, Jian; Yin, Tailang; Xiao, Xuwen; He, Dan; Xue, Zhidong; Jiang, Xinnong; Wang, Yan

2018-01-01

Abstract Bioactive peptides, with a variety of biological activities and wide distribution in nature, have attracted great research interest in biological and medical fields, especially in pharmaceutical industry. The structural information of bioactive peptide is important for the development of peptide-based drugs. Many databases have been developed cataloguing bioactive peptides. However, to our knowledge, database dedicated to collect all the bioactive peptides with known structure is not available yet. Thus, we developed StraPep, a structure database of bioactive peptides. StraPep holds 3791 bioactive peptide structures, which belong to 1312 unique bioactive peptide sequences. About 905 out of 1312 (68%) bioactive peptides in StraPep contain disulfide bonds, which is significantly higher than that (21%) of PDB. Interestingly, 150 out of 616 (24%) bioactive peptides with three or more disulfide bonds form a structural motif known as cystine knot, which confers considerable structural stability on proteins and is an attractive scaffold for drug design. Detailed information of each peptide, including the experimental structure, the location of disulfide bonds, secondary structure, classification, post-translational modification and so on, has been provided. A wide range of user-friendly tools, such as browsing, sequence and structure-based searching and so on, has been incorporated into StraPep. We hope that this database will be helpful for the research community. Database URL: http://isyslab.info/StraPep PMID:29688386

Large-scale extraction of accurate drug-disease treatment pairs from biomedical literature for drug repurposing

PubMed Central

2013-01-01

Background A large-scale, highly accurate, machine-understandable drug-disease treatment relationship knowledge base is important for computational approaches to drug repurposing. The large body of published biomedical research articles and clinical case reports available on MEDLINE is a rich source of FDA-approved drug-disease indication as well as drug-repurposing knowledge that is crucial for applying FDA-approved drugs for new diseases. However, much of this information is buried in free text and not captured in any existing databases. The goal of this study is to extract a large number of accurate drug-disease treatment pairs from published literature. Results In this study, we developed a simple but highly accurate pattern-learning approach to extract treatment-specific drug-disease pairs from 20 million biomedical abstracts available on MEDLINE. We extracted a total of 34,305 unique drug-disease treatment pairs, the majority of which are not included in existing structured databases. Our algorithm achieved a precision of 0.904 and a recall of 0.131 in extracting all pairs, and a precision of 0.904 and a recall of 0.842 in extracting frequent pairs. In addition, we have shown that the extracted pairs strongly correlate with both drug target genes and therapeutic classes, therefore may have high potential in drug discovery. Conclusions We demonstrated that our simple pattern-learning relationship extraction algorithm is able to accurately extract many drug-disease pairs from the free text of biomedical literature that are not captured in structured databases. The large-scale, accurate, machine-understandable drug-disease treatment knowledge base that is resultant of our study, in combination with pairs from structured databases, will have high potential in computational drug repurposing tasks. PMID:23742147

Oil and drug control the release rate from lyotropic liquid crystals.

PubMed

Martiel, Isabelle; Baumann, Nicole; Vallooran, Jijo J; Bergfreund, Jotam; Sagalowicz, Laurent; Mezzenga, Raffaele

2015-04-28

The control of the diffusion coefficient by the dimensionality d of the structure appears as a most promising lever to efficiently tune the release rate from lyotropic liquid crystalline (LLC) phases and dispersed particles towards sustained, controlled and targeted release. By using phosphatidylcholine (PC)- and monolinoleine (MLO)-based mesophases with various apolar structural modifiers and water-soluble drugs, we present a comprehensive study of the dimensional structural control of hydrophilic drug release, including 3-d bicontinuous cubic, 2-d lamellar, 1-d hexagonal and 0-d micellar cubic phases in excess water. We investigate how the surfactant, the oil properties and the drug hydrophilicity mitigate or even cancel the effect of structure variation on the drug release rate. Unexpectedly, the observed behavior cannot be fully explained by the thermodynamic partition of the drug into the lipid matrix, which points out to previously overlooked kinetic effects. We therefore interpret our results by discussing the mechanism of structural control of the diffusion rate in terms of drug permeation through the lipid membrane, which includes exchange kinetics. A wide range of implications follow regarding formulation and future developments, both for dispersed LLC delivery systems and topical applications in bulk phase. Copyright © 2015 Elsevier B.V. All rights reserved.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Docking and scoring in virtual screening for drug discovery: methods and applications.

PubMed

Kitchen, Douglas B; Decornez, Hélène; Furr, John R; Bajorath, Jürgen

2004-11-01

Computational approaches that 'dock' small molecules into the structures of macromolecular targets and 'score' their potential complementarity to binding sites are widely used in hit identification and lead optimization. Indeed, there are now a number of drugs whose development was heavily influenced by or based on structure-based design and screening strategies, such as HIV protease inhibitors. Nevertheless, there remain significant challenges in the application of these approaches, in particular in relation to current scoring schemes. Here, we review key concepts and specific features of small-molecule-protein docking methods, highlight selected applications and discuss recent advances that aim to address the acknowledged limitations of established approaches.

Mass spectrometry-driven drug discovery for development of herbal medicine.

PubMed

Zhang, Aihua; Sun, Hui; Wang, Xijun

2018-05-01

Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes. © 2016 Wiley Periodicals, Inc.

Computer-aided design of liposomal drugs: In silico prediction and experimental validation of drug candidates for liposomal remote loading.

PubMed

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-10

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs' structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al., J. Control. Release 160 (2012) 147-157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-Nearest Neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used by us in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. © 2013.

e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design.

PubMed

Pihan, Emilie; Colliandre, Lionel; Guichou, Jean-François; Douguet, Dominique

2012-06-01

In the drug discovery field, new uses for old drugs, selective optimization of side activities and fragment-based drug design (FBDD) have proved to be successful alternatives to high-throughput screening. e-Drug3D is a database of 3D chemical structures of drugs that provides several collections of ready-to-screen SD files of drugs and commercial drug fragments. They are natural inputs in studies dedicated to drug repurposing and FBDD. e-Drug3D collections are freely available at http://chemoinfo.ipmc.cnrs.fr/e-drug3d.html either for download or for direct in silico web-based screenings.

Silk-Based Biomaterials for Sustained Drug Delivery

PubMed Central

Yucel, Tuna; Lovett, Michael L.; Kaplan, David L.

2014-01-01

Silk presents a rare combination of desirable properties for sustained drug delivery, including aqueous-based purification and processing options without chemical cross-linkers, compatibility with common sterilization methods, controllable and surface-mediated biodegradation into non-inflammatory by-products, biocompatibility, utility in drug stabilization, and robust mechanical properties. A versatile silk-based toolkit is currently available for sustained drug delivery formulations of small molecule through macromolecular drugs, with a promise to mitigate several drawbacks associated with other degradable sustained delivery technologies in the market. Silk-based formulations utilize silk’s well-defined nano- through microscale structural hierarchy, stimuli-responsive self-assembly pathways and crystal polymorphism, as well as sequence and genetic modification options towards targeted pharmaceutical outcomes. Furthermore, by manipulating the interactions between silk and drug molecules, near-zero order sustained release may be achieved through diffusion- and degradation-based release mechanisms. Because of these desirable properties, there has been increasing industrial interest in silk-based drug delivery systems currently at various stages of the developmental pipeline from pre-clinical to FDA-approved products. Here, we discuss the unique aspects of silk technology as a sustained drug delivery platform and highlight the current state of the art in silk-based drug delivery. We also offer a potential early development pathway for silk-based sustained delivery products. PMID:24910193

Computational modeling-based discovery of novel classes of anti-inflammatory drugs that target lanthionine synthetase C-like protein 2.

PubMed

Lu, Pinyi; Hontecillas, Raquel; Horne, William T; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R; Lewis, Stephanie N; Bassaganya-Riera, Josep

2012-01-01

Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates.

Computational Modeling-Based Discovery of Novel Classes of Anti-Inflammatory Drugs That Target Lanthionine Synthetase C-Like Protein 2

PubMed Central

Lu, Pinyi; Hontecillas, Raquel; Horne, William T.; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R.; Lewis, Stephanie N.; Bassaganya-Riera, Josep

2012-01-01

Background Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. Methodology/Principal Findings The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. Conclusions/Significance LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates. PMID:22509338

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

Antiviral Information Management System (AIMS): a prototype for operational innovation in drug development.

PubMed

Jadhav, Pravin R; Neal, Lauren; Florian, Jeff; Chen, Ying; Naeger, Lisa; Robertson, Sarah; Soon, Guoxing; Birnkrant, Debra

2010-09-01

This article presents a prototype for an operational innovation in knowledge management (KM). These operational innovations are geared toward managing knowledge efficiently and accessing all available information by embracing advances in bioinformatics and allied fields. The specific components of the proposed KM system are (1) a database to archive hepatitis C virus (HCV) treatment data in a structured format and retrieve information in a query-capable manner and (2) an automated analysis tool to inform trial design elements for HCV drug development. The proposed framework is intended to benefit drug development by increasing efficiency of dose selection and improving the consistency of advice from US Food and Drug Administration (FDA). It is also hoped that the framework will encourage collaboration among FDA, industry, and academic scientists to guide the HCV drug development process using model-based quantitative analysis techniques.

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

An Ensemble Approach for Drug Side Effect Prediction

PubMed Central

Jahid, Md Jamiul; Ruan, Jianhua

2014-01-01

In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have similar side-effects. Based on this observation we design an ensemble approach that combine the results from different classification models where each model is generated by a different set of similar drugs. We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. Results from various sources confirm that our method is able to predict the side-effects for uncharacterized drugs and more importantly able to predict rare side-effects which are often ignored by other approaches. The method described in this article can be useful to predict side-effects in drug design in an early stage to reduce experimental cost and time. PMID:25327524

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens

PubMed Central

Sosa, Ezequiel J; Burguener, Germán; Lanzarotti, Esteban; Radusky, Leandro; Pardo, Agustín M; Marti, Marcelo

2018-01-01

Abstract Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request. PMID:29106651

Description of a drug hierarchy in a concept-based reference terminology.

PubMed Central

Kim, J. M.; Frosdick, P.

2001-01-01

A concept-based reference terminology that covers all aspects of healthcare is essential in developing the Electronic Health Record (EHR). SNOMED Clinical Terms (CT), scheduled for release in December 2001, integrates the relative strengths of SNOMED RT, and the United Kingdom s Clinical Terms Version 3, formerly known as the Read Codes Version 3. It promises to be the most comprehensive terminology available. Since a significant portion of the EHR can be drug-related information, we describe here some of the background information and rationale for the structure and scope of the merged drug hierarchy within SNOMED CT. A controlled drug terminology within a reference terminology has the potential to support a number of functions within healthcare practice. One of the functions proposed is to serve as the bridge between reference terminology and drug knowledge bases. PMID:11825202

Nanostructure-mediated drug delivery.

PubMed

Hughes, Gareth A

2005-03-01

Nanotechnology is expected to have an impact on all industries including semiconductors, manufacturing, and biotechnology. Tools that provide the capability to characterize and manipulate materials at the nanoscale level further elucidate nanoscale phenomena and equip researchers and developers with the ability to fabricate novel materials and structures. One of the most promising societal impacts of nanotechnology is in the area of nanomedicine. Personalized health care, rational drug design, and targeted drug delivery are some of the benefits of a nanomedicine-based approach to therapy. This review will focus on the development of nanoscale drug delivery mechanisms. Nanostructured drug carriers allow for the delivery of not only small-molecule drugs but also the delivery of nucleic acids and proteins. Delivery of these molecules to specific areas within the body can be achieved, which will reduce systemic side effects and allow for more efficient use of the drug.

Successful applications of computer aided drug discovery: moving drugs from concept to the clinic.

PubMed

Talele, Tanaji T; Khedkar, Santosh A; Rigby, Alan C

2010-01-01

Drug discovery and development is an interdisciplinary, expensive and time-consuming process. Scientific advancements during the past two decades have changed the way pharmaceutical research generate novel bioactive molecules. Advances in computational techniques and in parallel hardware support have enabled in silico methods, and in particular structure-based drug design method, to speed up new target selection through the identification of hits to the optimization of lead compounds in the drug discovery process. This review is focused on the clinical status of experimental drugs that were discovered and/or optimized using computer-aided drug design. We have provided a historical account detailing the development of 12 small molecules (Captopril, Dorzolamide, Saquinavir, Zanamivir, Oseltamivir, Aliskiren, Boceprevir, Nolatrexed, TMI-005, LY-517717, Rupintrivir and NVP-AUY922) that are in clinical trial or have become approved for therapeutic use.

Silica Materials for Medical Applications

PubMed Central

Vallet-Regí, María; Balas, Francisco

2008-01-01

The two main applications of silica-based materials in medicine and biotechnology, i.e. for bone-repairing devices and for drug delivery systems, are presented and discussed. The influence of the structure and chemical composition in the final characteristics and properties of every silica-based material is also shown as a function of the both applications presented. The adequate combination of the synthesis techniques, template systems and additives leads to the development of materials that merge the bioactive behavior with the drug carrier ability. These systems could be excellent candidates as materials for the development of devices for tissue engineering. PMID:19662110

Can Functional Magnetic Resonance Imaging Improve Success Rates in CNS Drug Discovery?

PubMed Central

Borsook, David; Hargreaves, Richard; Becerra, Lino

2011-01-01

Introduction The bar for developing new treatments for CNS disease is getting progressively higher and fewer novel mechanisms are being discovered, validated and developed. The high costs of drug discovery necessitate early decisions to ensure the best molecules and hypotheses are tested in expensive late stage clinical trials. The discovery of brain imaging biomarkers that can bridge preclinical to clinical CNS drug discovery and provide a ‘language of translation’ affords the opportunity to improve the objectivity of decision-making. Areas Covered This review discusses the benefits, challenges and potential issues of using a science based biomarker strategy to change the paradigm of CNS drug development and increase success rates in the discovery of new medicines. The authors have summarized PubMed and Google Scholar based publication searches to identify recent advances in functional, structural and chemical brain imaging and have discussed how these techniques may be useful in defining CNS disease state and drug effects during drug development. Expert opinion The use of novel brain imaging biomarkers holds the bold promise of making neuroscience drug discovery smarter by increasing the objectivity of decision making thereby improving the probability of success of identifying useful drugs to treat CNS diseases. Functional imaging holds the promise to: (1) define pharmacodynamic markers as an index of target engagement (2) improve translational medicine paradigms to predict efficacy; (3) evaluate CNS efficacy and safety based on brain activation; (4) determine brain activity drug dose-response relationships and (5) provide an objective evaluation of symptom response and disease modification. PMID:21765857

Specific Stereoisomeric Conformations Determine the Drug Potency of Cladosporin Scaffold against Malarial Parasite.

PubMed

Das, Pronay; Babbar, Palak; Malhotra, Nipun; Sharma, Manmohan; Jachak, Gorakhnath R; Gonnade, Rajesh G; Shanmugam, Dhanasekaran; Harlos, Karl; Yogavel, Manickam; Sharma, Amit; Reddy, D Srinivasa

2018-05-21

The dependence of drug potency on diastereomeric configurations is a key facet. Using a novel general divergent synthetic route for a three-chiral centre anti-malarial natural product cladosporin, we built its complete library of stereoisomers (cladologs) and assessed their inhibitory potential using parasite-, enzyme- and structure-based assays. We show that potency is manifest via tetrahyropyran ring conformations that are housed in the ribose binding pocket of parasite lysyl tRNA synthetase (KRS). Strikingly, drug potency between top and worst enantiomers varied 500-fold, and structures of KRS-cladolog complexes reveal that alterations at C3 and C10 are detrimental to drug potency where changes at C3 are sensed by rotameric flipping of Glutamate332. Given that scores of anti-malarial and anti-infective drugs contain chiral centers, this work provides a new foundation for focusing on inhibitor stereochemistry as a facet of anti-microbial drug development.

DOTAM derivatives as active cartilage-targeting drug carriers for the treatment of osteoarthritis.

PubMed

Hu, Hai-Yu; Lim, Ngee-Han; Ding-Pfennigdorff, Danping; Saas, Joachim; Wendt, K Ulrich; Ritzeler, Olaf; Nagase, Hideaki; Plettenburg, Oliver; Schultz, Carsten; Nazare, Marc

2015-03-18

Targeted drug-delivery methods are crucial for effective treatment of degenerative joint diseases such as osteoarthritis (OA). Toward this goal, we developed a small multivalent structure as a model drug for the attenuation of cartilage degradation. The DOTAM (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid amide)-based model structure is equipped with the cathepsin D protease inhibitor pepstatin A, a fluorophore, and peptide moieties targeting collagen II. In vivo injection of these soluble probes into the knee joints of mice resulted in 7-day-long local retention, while the drug carrier equipped with a scrambled peptide sequence was washed away within 6-8 h. The model drug conjugate successfully reduced the cathepsin D protease activity as measured by release of GAG peptide. Therefore, these conjugates represent a promising first drug conjugate for the targeted treatment of degenerative joint diseases.

The Development of CK2 Inhibitors: From Traditional Pharmacology to in Silico Rational Drug Design

PubMed Central

Cozza, Giorgio

2017-01-01

Casein kinase II (CK2) is an ubiquitous and pleiotropic serine/threonine protein kinase able to phosphorylate hundreds of substrates. Being implicated in several human diseases, from neurodegeneration to cancer, the biological roles of CK2 have been intensively studied. Upregulation of CK2 has been shown to be critical to tumor progression, making this kinase an attractive target for cancer therapy. Several CK2 inhibitors have been developed so far, the first being discovered by “trial and error testing”. In the last decade, the development of in silico rational drug design has prompted the discovery, de novo design and optimization of several CK2 inhibitors, active in the low nanomolar range. The screening of big chemical libraries and the optimization of hit compounds by Structure Based Drug Design (SBDD) provide telling examples of a fruitful application of rational drug design to the development of CK2 inhibitors. Ligand Based Drug Design (LBDD) models have been also applied to CK2 drug discovery, however they were mainly focused on methodology improvements rather than being critical for de novo design and optimization. This manuscript provides detailed description of in silico methodologies whose applications to the design and development of CK2 inhibitors proved successful and promising. PMID:28230762

Pharmacology Goes Concept-Based: Course Design, Implementation, and Evaluation.

PubMed

Lanz, Amelia; Davis, Rebecca G

Although concept-based curricula are frequently discussed in the nursing education literature, little information exists to guide the development of a concept-based pharmacology course. Traditionally, nursing pharmacology courses are taught with an emphasis on drug class where a prototype drug serves as an exemplar. When transitioning pharmacology to a concept-based course, special considerations are in order. How can educators successfully integrate essential pharmacological content into a curriculum structured around nursing concepts? This article presents one approach to the design and implementation of a concept-based undergraduate pharmacology course. Planning methods, supportive teaching strategies, and course evaluation procedures are discussed.

Conformational Analysis of Drug Molecules: A Practical Exercise in the Medicinal Chemistry Course

ERIC Educational Resources Information Center

Yuriev, Elizabeth; Chalmers, David; Capuano, Ben

2009-01-01

Medicinal chemistry is a specialized, scientific discipline. Computational chemistry and structure-based drug design constitute important themes in the education of medicinal chemists. This problem-based task is associated with structure-based drug design lectures. It requires students to use computational techniques to investigate conformational…

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

A novel integrated framework and improved methodology of computer-aided drug design.

PubMed

Chen, Calvin Yu-Chian

2013-01-01

Computer-aided drug design (CADD) is a critical initiating step of drug development, but a single model capable of covering all designing aspects remains to be elucidated. Hence, we developed a drug design modeling framework that integrates multiple approaches, including machine learning based quantitative structure-activity relationship (QSAR) analysis, 3D-QSAR, Bayesian network, pharmacophore modeling, and structure-based docking algorithm. Restrictions for each model were defined for improved individual and overall accuracy. An integration method was applied to join the results from each model to minimize bias and errors. In addition, the integrated model adopts both static and dynamic analysis to validate the intermolecular stabilities of the receptor-ligand conformation. The proposed protocol was applied to identifying HER2 inhibitors from traditional Chinese medicine (TCM) as an example for validating our new protocol. Eight potent leads were identified from six TCM sources. A joint validation system comprised of comparative molecular field analysis, comparative molecular similarity indices analysis, and molecular dynamics simulation further characterized the candidates into three potential binding conformations and validated the binding stability of each protein-ligand complex. The ligand pathway was also performed to predict the ligand "in" and "exit" from the binding site. In summary, we propose a novel systematic CADD methodology for the identification, analysis, and characterization of drug-like candidates.

Drug-Drug Multicomponent Solid Forms: Cocrystal, Coamorphous and Eutectic of Three Poorly Soluble Antihypertensive Drugs Using Mechanochemical Approach.

PubMed

Haneef, Jamshed; Chadha, Renu

2017-08-01

The present study deals with the application of mechanochemical approach for the preparation of drug-drug multicomponent solid forms of three poorly soluble antihypertensive drugs (telmisartan, irbesartan and hydrochlorothiazide) using atenolol as a coformer. The resultant solid forms comprise of cocrystal (telmisartan-atenolol), coamorphous (irbesartan-atenolol) and eutectic (hydrochlorothiazide-atenolol). The study emphasizes that solid-state transformation of drug molecules into new forms is a result of the change in structural patterns, diminishing of dimers and creating new facile hydrogen bonding network based on structural resemblance. The propensity for heteromeric or homomeric interaction between two different drugs resulted into diverse solid forms (cocrystal/coamorphous/eutectics) and become one of the interesting aspects of this research work. Evaluation of these solid forms revealed an increase in solubility and dissolution leading to better antihypertensive activity in deoxycorticosterone acetate (DOCA) salt-induced animal model. Thus, development of these drug-drug multicomponent solid forms is a promising and viable approach to addressing the issue of poor solubility and could be of considerable interest in dual drug therapy for the treatment of hypertension.

Local anesthetic and antiepileptic drug access and binding to a bacterial voltage-gated sodium channel

PubMed Central

Boiteux, Céline; Vorobyov, Igor; French, Robert J.; French, Christopher; Yarov-Yarovoy, Vladimir; Allen, Toby W.

2014-01-01

Voltage-gated sodium (Nav) channels are important targets in the treatment of a range of pathologies. Bacterial channels, for which crystal structures have been solved, exhibit modulation by local anesthetic and anti-epileptic agents, allowing molecular-level investigations into sodium channel-drug interactions. These structures reveal no basis for the “hinged lid”-based fast inactivation, seen in eukaryotic Nav channels. Thus, they enable examination of potential mechanisms of use- or state-dependent drug action based on activation gating, or slower pore-based inactivation processes. Multimicrosecond simulations of NavAb reveal high-affinity binding of benzocaine to F203 that is a surrogate for FS6, conserved in helix S6 of Domain IV of mammalian sodium channels, as well as low-affinity sites suggested to stabilize different states of the channel. Phenytoin exhibits a different binding distribution owing to preferential interactions at the membrane and water–protein interfaces. Two drug-access pathways into the pore are observed: via lateral fenestrations connecting to the membrane lipid phase, as well as via an aqueous pathway through the intracellular activation gate, despite being closed. These observations provide insight into drug modulation that will guide further developments of Nav inhibitors. PMID:25136136

Surfactant-based drug delivery systems for treating drug-resistant lung cancer.

PubMed

Kaur, Prabhjot; Garg, Tarun; Rath, Goutam; Murthy, R S R; Goyal, Amit K

2016-01-01

Among all cancers, lung cancer is the major cause of deaths. Lung cancer can be categorized into two classes for prognostic and treatment purposes: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Both categories of cancer are resistant to certain drugs. Various mechanisms behind drug resistance are over-expression of superficial membrane proteins [glycoprotein (P-gp)], lung resistance-associated proteins, aberration of the intracellular enzyme system, enhancement of the cell repair system and deregulation of cell apoptosis. Structure-performance relationships and chemical compatibility are consequently major fundamentals in surfactant-based formulations, with the intention that a great deal investigation is committed to this region. With the purpose to understand the potential of P-gp in transportation of anti-tumor drugs to cancer cells with much effectiveness and specificity, several surfactant-based delivery systems have been developed which may include microspheres, nanosized drug carriers (nanoparticles, nanoemulsions, stealth liposomes, nanogels, polymer-drug conjugates), novel powders, hydrogels and mixed micellar systems intended for systemic and/or localized delivery.

Modeling the full length HIV-1 Gag polyprotein reveals the role of its p6 subunit in viral maturation and the effect of non-cleavage site mutations in protease drug resistance.

PubMed

Su, Chinh Tran-To; Kwoh, Chee-Keong; Verma, Chandra Shekhar; Gan, Samuel Ken-En

2017-12-27

HIV polyprotein Gag is increasingly found to contribute to protease inhibitor resistance. Despite its role in viral maturation and in developing drug resistance, there remain gaps in the knowledge of the role of certain Gag subunits (e.g. p6), and that of non-cleavage mutations in drug resistance. As p6 is flexible, it poses a problem for structural experiments, and is hence often omitted in experimental Gag structural studies. Nonetheless, as p6 is an indispensable component for viral assembly and maturation, we have modeled the full length Gag structure based on several experimentally determined constraints and studied its structural dynamics. Our findings suggest that p6 can mechanistically modulate Gag conformations. In addition, the full length Gag model reveals that allosteric communication between the non-cleavage site mutations and the first Gag cleavage site could possibly result in protease drug resistance, particularly in the absence of mutations in Gag cleavage sites. Our study provides a mechanistic understanding to the structural dynamics of HIV-1 Gag, and also proposes p6 as a possible drug target in anti-HIV therapy.

Mass Spectrometry Imaging of Drug Related Crystal-Like Structures in Formalin-Fixed Frozen and Paraffin-Embedded Rabbit Kidney Tissue Sections

NASA Astrophysics Data System (ADS)

Bruinen, Anne L.; van Oevelen, Cateau; Eijkel, Gert B.; Van Heerden, Marjolein; Cuyckens, Filip; Heeren, Ron M. A.

2016-01-01

A multimodal mass spectrometry imaging (MSI) based approach was used to characterize the molecular content of crystal-like structures in a frozen and paraffin embedded piece of a formalin-fixed rabbit kidney. Matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging and desorption electrospray ionization (DESI) mass spectrometry imaging were combined to analyze the frozen and paraffin embedded sample without further preparation steps to remove the paraffin. The investigated rabbit kidney was part of a study on a drug compound in development, in which severe renal toxicity was observed in dosed rabbits. Histological examination of the kidney showed tubular degeneration with precipitation of crystal-like structures in the cortex, which were assumed to cause the renal toxicity. The MS imaging approach was used to find out whether the crystal-like structures were composed of the drug compound, metabolites, or an endogenous compound as a reaction to the drug administration. The generated MALDI-MSI data were analyzed using principal component analysis. In combination with the MS/MS results, this way of data processing demonstrates that the crystal structures were mainly composed of metabolites and relatively little parent drug.

pH-driven colloidal transformations based on the vasoactive drug nicergoline.

PubMed

Salentinig, Stefan; Tangso, Kristian J; Hawley, Adrian; Boyd, Ben J

2014-12-16

The structure of colloidal self-assembled drug delivery systems can be influenced by intermolecular interactions between drug and amphiphilic molecules, and is important to understand in the context of designing improved delivery systems. Controlling these structures can enable controlled or targeted release systems for poorly water-soluble drugs. Here we present the interaction of the hydrophobic vasoactive drug nicergoline with the internal structure of nanostructured emulsion particles based on the monoglyceride-water system. Addition of this drug leads to modification of the internal bicontinuous cubic structure to generate highly pH-responsive systems. The colloidal structures were characterized with small-angle X-ray scattering and visualized using cryogenic transmission electron microscopy. Reversible transformations to inverse micelles at high pH, vesicles at low pH, and the modification of the spacing of the bicontinuous cubic structure at intermediate pH were observed, and enabled the in situ determination of an apparent pKa for the drug in this system--a difficult task using solution-based approaches. The characterization of this phase behavior is also highly interesting for the design of pH-responsive controlled release systems for poorly water-soluble drug molecules.

Drug delivery with microsecond laser pulses into gelatin.

PubMed

Shangguan, H; Casperson, L W; Shearin, A; Gregory, K W; Prahl, S A

1996-07-01

Photo acoustic drug delivery is a technique for localized drug delivery by laser-induced hydrodynamic pressure following cavitation bubble expansion and collapse. Photoacoustic drug delivery was investigated on gelatin-based thrombus models with planar and cylindrical geometries by use of one microsecond laser pulses. Solutions of a hydrophobic dye in mineral oil permitted monitoring of delivered colored oil into clear gelatin-based thrombus models. Cavitation bubble development and photoacoustic drug delivery were visualized with flash photography. This study demonstrated that cavitation is the governing mechanism for photoacoustic drug delivery, and the deepest penetration of colored oil in gels followed the bubble collapse. Spatial distribution measurements revealed that colored oil could be driven a few millimeters into the gels in both axial and radial directions, and the penetration was less than 500 µm when the gelatin structure was not fractured.

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Computer-aided design of liposomal drugs: in silico prediction and experimental validation of drug candidates for liposomal remote loading

PubMed Central

Cern, Ahuva; Barenholz, Yechezkel; Tropsha, Alexander; Goldblum, Amiram

2014-01-01

Previously we have developed and statistically validated Quantitative Structure Property Relationship (QSPR) models that correlate drugs’ structural, physical and chemical properties as well as experimental conditions with the relative efficiency of remote loading of drugs into liposomes (Cern et al, Journal of Controlled Release, 160(2012) 14–157). Herein, these models have been used to virtually screen a large drug database to identify novel candidate molecules for liposomal drug delivery. Computational hits were considered for experimental validation based on their predicted remote loading efficiency as well as additional considerations such as availability, recommended dose and relevance to the disease. Three compounds were selected for experimental testing which were confirmed to be correctly classified by our previously reported QSPR models developed with Iterative Stochastic Elimination (ISE) and k-nearest neighbors (kNN) approaches. In addition, 10 new molecules with known liposome remote loading efficiency that were not used in QSPR model development were identified in the published literature and employed as an additional model validation set. The external accuracy of the models was found to be as high as 82% or 92%, depending on the model. This study presents the first successful application of QSPR models for the computer-model-driven design of liposomal drugs. PMID:24184343

Drug delivery with microsecond laser pulses into gelatin

NASA Astrophysics Data System (ADS)

Shangguan, Hanqun; Casperson, Lee W.; Shearin, Alan; Gregory, Kenton W.; Prahl, Scott A.

1996-07-01

Photoacoustic drug delivery is a technique for localized drug delivery by laser-induced hydrodynamic pressure following cavitation bubble expansion and collapse. Photoacoustic drug delivery was investigated on gelatin-based thrombus models with planar and cylindrical geometries by use of one microsecond laser pulses. Solutions of a hydrophobic dye in mineral oil permitted monitoring of delivered colored oil into clear gelatin-based thrombus models. Cavitation bubble development and photoacoustic drug delivery were visualized with flash photography. This study demonstrated that cavitation is the governing mechanism for photoacoustic drug delivery, and the deepest penetration of colored oil in gels followed the bubble collapse. Spatial distribution measurements revealed that colored oil could be driven a few millimeters into the gels in both axial and radial directions, and the penetration was less than 500 mu m when the gelatin structure was not fractured. localized drug delivery, cavitation bubble, laser thrombolysis.

Hydrogels for Hydrophobic Drug Delivery. Classification, Synthesis and Applications

PubMed Central

Stewart, Sarah; Ervine, Michael; Al-Kasasbeh, Rehan; Donnelly, Ryan F.

2018-01-01

Hydrogels have been shown to be very useful in the field of drug delivery due to their high biocompatibility and ability to sustain delivery. Therefore, the tuning of their properties should be the focus of study to optimise their potential. Hydrogels have been generally limited to the delivery of hydrophilic drugs. However, as many of the new drugs coming to market are hydrophobic in nature, new approaches for integrating hydrophobic drugs into hydrogels should be developed. This article discusses the possible new ways to incorporate hydrophobic drugs within hydrogel structures that have been developed through research. This review describes hydrogel-based systems for hydrophobic compound delivery included in the literature. The section covers all the main types of hydrogels, including physical hydrogels and chemical hydrogels. Additionally, reported applications of these hydrogels are described in the subsequent sections. PMID:29364833

The clinical development of p53-reactivating drugs in sarcomas - charting future therapeutic approaches and understanding the clinical molecular toxicology of Nutlins.

PubMed

Biswas, Swethajit; Killick, Emma; Jochemsen, Aart G; Lunec, John

2014-05-01

The majority of human sarcomas, particularly soft tissue sarcomas, are relatively resistant to traditional cytotoxic therapies. The proof-of-concept study by Ray-Coquard et al., using the Nutlin human double minute (HDM)2-binding antagonist RG7112, has recently opened a new chapter in the molecular targeting of human sarcomas. In this review, the authors discuss the challenges and prospective remedies for minimizing the significant haematological toxicities of the cis-imidazole Nutlin HDM2-binding antagonists. Furthermore, they also chart the future direction of the development of p53-reactivating (p53-RA) drugs in 12q13-15 amplicon sarcomas and as potential chemopreventative therapies against sarcomagenesis in germ line mutated TP53 carriers. Drawing lessons from the therapeutic use of Imatinib in gastrointestinal tumours, the authors predict the potential pitfalls, which may lie in ahead for the future clinical development of p53-RA agents, as well as discussing potential non-invasive methods to identify the development of drug resistance. Medicinal chemistry strategies, based on structure-based drug design, are required to re-engineer cis-imidazoline Nutlin HDM2-binding antagonists into less haematologically toxic drugs. In silico modelling is also required to predict toxicities of other p53-RA drugs at a much earlier stage in drug development. Whether p53-RA drugs will be therapeutically effective as a monotherapy remains to be determined.

Mesoporous carbon nanomaterials in drug delivery and biomedical application.

PubMed

Zhao, Qinfu; Lin, Yuanzhe; Han, Ning; Li, Xian; Geng, Hongjian; Wang, Xiudan; Cui, Yu; Wang, Siling

2017-01-01

Recent development of nano-technology provides highly efficient and versatile treatment methods to achieve better therapeutic efficacy and lower side effects of malignant cancer. The exploration of drug delivery systems (DDSs) based on nano-material shows great promise in translating nano-technology to clinical use to benefit patients. As an emerging inorganic nanomaterial, mesoporous carbon nanomaterials (MCNs) possess both the mesoporous structure and the carbonaceous composition, endowing them with superior nature compared with mesoporous silica nanomaterials and other carbon-based materials, such as carbon nanotube, graphene and fullerene. In this review, we highlighted the cutting-edge progress of carbon nanomaterials as drug delivery systems (DDSs), including immediate/sustained drug delivery systems and controlled/targeted drug delivery systems. In addition, several representative biomedical applications of mesoporous carbon such as (1) photo-chemo synergistic therapy; (2) delivery of therapeutic biomolecule and (3) in vivo bioimaging are discussed and integrated. Finally, potential challenges and outlook for future development of mesoporous carbon in biomedical fields have been discussed in detail.

New approaches to structure-based discovery of dengue protease inhibitors.

PubMed

Tomlinson, S M; Malmstrom, R D; Watowich, S J

2009-06-01

Dengue virus (DENV), a member of the family Flaviviridae, presents a tremendous threat to global health since an estimated 2.5 billion people worldwide are at risk for epidemic transmission. DENV infections are primarily restricted to sub-tropical and tropical regions; however, there is concern that the virus will spread into new regions including the United States. There are no approved antiviral drugs or vaccines to combat dengue infection, although DENV vaccines have entered Phase 3 clinical trials. Drug discovery and development efforts against DENV and other viral pathogens must overcome specificity, efficacy, safety, and resistance challenges before the shortage of licensed drugs to treat viral infections can be relieved. Current drug discovery methods are largely inefficient and thus relatively ineffective at tackling the growing threat to public health presented by emerging and remerging viral pathogens. This review discusses current and newly implemented structure-based computational efforts to discover antivirals that target the DENV NS3 protease, although it is clear that these computational tools can be applied to most disease targets.

Advances in structural design of lipid-based nanoparticle carriers for delivery of macromolecular drugs, phytochemicals and anti-tumor agents.

PubMed

Angelova, Angelina; Garamus, Vasil M; Angelov, Borislav; Tian, Zhenfen; Li, Yawen; Zou, Aihua

2017-11-01

The present work highlights recent achievements in development of nanostructured dispersions and biocolloids for drug delivery applications. We emphasize the key role of biological small-angle X-ray scattering (BioSAXS) investigations for the nanomedicine design. A focus is given on controlled encapsulation of small molecular weight phytochemical drugs in lipid-based nanocarriers as well as on encapsulation of macromolecular siRNA, plasmid DNA, peptide and protein pharmaceuticals in nanostructured nanoparticles that may provide efficient intracellular delivery and triggered drug release. Selected examples of utilisation of the BioSAXS method for characterization of various types of liquid crystalline nanoorganizations (liposome, spongosome, cubosome, hexosome, and nanostructured lipid carriers) are discussed in view of the successful encapsulation and protection of phytochemicals and therapeutic biomolecules in the hydrophobic or the hydrophilic compartments of the nanocarriers. We conclude that the structural design of the nanoparticulate carriers is of crucial importance for the therapeutic outcome and the triggered drug release from biocolloids. Copyright © 2017 Elsevier B.V. All rights reserved.

The application of quantum mechanics in structure-based drug design.

PubMed

Mucs, Daniel; Bryce, Richard A

2013-03-01

Computational chemistry has become an established and valuable component in structure-based drug design. However the chemical complexity of many ligands and active sites challenges the accuracy of the empirical potentials commonly used to describe these systems. Consequently, there is a growing interest in utilizing electronic structure methods for addressing problems in protein-ligand recognition. In this review, the authors discuss recent progress in the development and application of quantum chemical approaches to modeling protein-ligand interactions. The authors specifically consider the development of quantum mechanics (QM) approaches for studying large molecular systems pertinent to biology, focusing on protein-ligand docking, protein-ligand binding affinities and ligand strain on binding. Although computation of binding energies remains a challenging and evolving area, current QM methods can underpin improved docking approaches and offer detailed insights into ligand strain and into the nature and relative strengths of complex active site interactions. The authors envisage that QM will become an increasingly routine and valued tool of the computational medicinal chemist.

Innovative polymeric system (IPS) for solvent-free lipophilic drug transdermal delivery via dissolving microneedles.

PubMed

Dangol, Manita; Yang, Huisuk; Li, Cheng Guo; Lahiji, Shayan Fakhraei; Kim, Suyong; Ma, Yonghao; Jung, Hyungil

2016-02-10

Lipophilic drugs are potential drug candidates during drug development. However, due to the need for hazardous organic solvents for their solubilization, these drugs often fail to reach the pharmaceutical market, and in doing so highlight the importance of solvent free systems. Although transdermal drug delivery systems (TDDSs) are considered prospective safe drug delivery routes, a system involving lipophilic drugs in solvent free or powder form has not yet been described. Here, we report, for the first time, a novel approach for the delivery of every kind of lipophilic drug in powder form based on an innovative polymeric system (IPS). The phase transition of powder form of lipophilic drugs due to interior chemical bonds between drugs and biodegradable polymers and formation of nano-sized colloidal structures allowed the fabrication of dissolving microneedles (DMNs) to generate a powerful TDDS. We showed that IPS based DMN with powder capsaicin enhances the therapeutic effect for treatment of the rheumatic arthritis in a DBA/1 mouse model compared to a solvent-based system, indicating the promising potential of this new solvent-free platform for lipophilic drug delivery. Copyright © 2016 Elsevier B.V. All rights reserved.

Design, Synthesis, and Characterization of Novel Zwitterionic Lipids for Drug and siRNA Delivery Applications

NASA Astrophysics Data System (ADS)

Walsh, Colin L.

Lipid-based nanoparticles have long been used to deliver biologically active molecules such as drugs, proteins, peptides, DNA, and siRNA in vivo. Liposomes and lipoplexes alter the biodistribution, pharmacokinetics, and cellular uptake of their encapsulated or associated cargo. This can increase drug efficacy while reducing toxicity, resulting in an increased therapeutic index and better clinical outcomes. Unlike small molecule drugs, which passively diffuse through lipid membranes, nucleic acids and proteins require an active, carrier mediated escape mechanism to reach their site of action. As such, the therapeutic application and drug properties dictate the required biophysical characteristics of the lipid nanoparticle. These carrier properties depend on the structure and biophysical characteristics of the lipids and other components used to formulate them. This dissertation presents a series of studies related to the development of novel synthetic lipids for use in drug delivery systems. First, we developed a novel class of zwitterionic lipids with head groups containing a cationic amine and anionic carboxylate and ester-linked oleic acid tails. These lipids exhibit structure-dependent, pH-responsive biophysical properties, and may be useful components for next-generation drug delivery systems. Second, we extended the idea of amine/carboxylate containing zwitterionic head groups and synthesized a series of acetate terminated diacyl lipids containing a quaternary amine. These lipids have an inverted headgroup orientation compared to naturally occurring zwitterionic lipids, and show interesting salt-dependent biophysical properties. Third, we synthesized and characterized a focused library of ionizable lysine-based lipids, which contain a lysine head group linked to a long-chain dialkylamine. A focused library was synthesized to determine the impact of hydrophobic fluidity, lipid net charge, and lipid pKa on the biophysical and siRNA transfection characteristics of these lipids. Our results indicate that structural variations significantly impact the biophysical and transfection behavior of this class of lipids. In summary, we have synthesized several new classes of lipids with biophysical characteristics that may be useful for drug delivery applications. Our results show that slight modifications to lipid structure impacts their biophysical behavior, which in turn dictates their potential utility in drug delivery systems. Further understanding lipid structure-activity relationships will allow for the rational design and engineering of lipids with appropriate properties for specific delivery applications.

Drugs for Neglected Diseases initiative model of drug development for neglected diseases: current status and future challenges.

PubMed

Ioset, Jean-Robert; Chang, Shing

2011-09-01

The Drugs for Neglected Diseases initiative (DNDi) is a patients' needs-driven organization committed to the development of new treatments for neglected diseases. Created in 2003, DNDi has delivered four improved treatments for malaria, sleeping sickness and visceral leishmaniasis. A main DNDi challenge is to build a solid R&D portfolio for neglected diseases and to deliver preclinical candidates in a timely manner using an original model based on partnership. To address this challenge DNDi has remodeled its discovery activities from a project-based academic-bound network to a fully integrated process-oriented platform in close collaboration with pharmaceutical companies. This discovery platform relies on dedicated screening capacity and lead-optimization consortia supported by a pragmatic, structured and pharmaceutical-focused compound sourcing strategy.

The right drug, but from whose perspective? A framework for analysing the structure and activities of drug and therapeutics committees.

PubMed

Hoffmann, Mikael

2013-05-01

During the last five decades drug and therapeutics committees (DTCs), have evolved from mainly hospital-based groups of experts in pharmacotherapy and drug logistics into an arena for healthcare professionals employing evidence-based methods of promoting rational drug use. The purpose of this study was to suggest a framework for analysing the structure and activities of DTCs. A literature search was carried out in the Medline, Cinahl and Web of Sciences databases for the period 1993-2012. A total of 207 articles were included. Based on these articles a framework for the analysis of the DTCs based on the role of the DTC, target groups, budget perspective and type of economic decisions could be suggested. In order to respond to future demands the DTCs will have to develop their skill in pharmacoeconomics. Their processes will have to be standardised and made more transparent in order to be better adapted to evidence-based decision-making. They will also have to embrace the possibilities created by electronic health records in both influencing the decisions of physicians, and in improving quality assurance programmes and longitudinal follow-up of drug therapy and outcomes. They will have to find new ways of interacting with the public and policy makers in order to get the resources needed for their work. Finally, they will have to handle the conflict among national, regional and local decision-making processes and the relationship between formularies and therapeutic guidelines.

Nanodiamond-Based Composite Structures for Biomedical Imaging and Drug Delivery.

PubMed

Rosenholm, Jessica M; Vlasov, Igor I; Burikov, Sergey A; Dolenko, Tatiana A; Shenderova, Olga A

2015-02-01

Nanodiamond particles are widely recognized candidates for biomedical applications due to their excellent biocompatibility, bright photoluminescence based on color centers and outstanding photostability. Recently, more complex architectures with a nanodiamond core and an external shell or nanostructure which provides synergistic benefits have been developed, and their feasibility for biomedical applications has been demonstrated. This review is aimed at summarizing recent achievements in the fabrication and functional demonstrations of nanodiamond-based composite structures, along with critical considerations that should be taken into account in the design of such structures from a biomedical point of view. A particular focus of the review is core/shell structures of nanodiamond surrounded by porous silica shells, which demonstrate a remarkable increase in drug loading efficiency; as well as nanodiamonds decorated with carbon dots, which have excellent potential as bioimaging probes. Other combinations are also considered, relying on the discussed inherent properties of the inorganic materials being integrated in a way to advance inorganic nanomedicine in the quest for better health-related nanotechnology.

Targeting Prolyl-tRNA Synthetase to Accelerate Drug Discovery against Malaria, Leishmaniasis, Toxoplasmosis, Cryptosporidiosis, and Coccidiosis.

PubMed

Jain, Vitul; Yogavel, Manickam; Kikuchi, Haruhisa; Oshima, Yoshiteru; Hariguchi, Norimitsu; Matsumoto, Makoto; Goel, Preeti; Touquet, Bastien; Jumani, Rajiv S; Tacchini-Cottier, Fabienne; Harlos, Karl; Huston, Christopher D; Hakimi, Mohamed-Ali; Sharma, Amit

2017-10-03

Developing anti-parasitic lead compounds that act on key vulnerabilities are necessary for new anti-infectives. Malaria, leishmaniasis, toxoplasmosis, cryptosporidiosis and coccidiosis together kill >500,000 humans annually. Their causative parasites Plasmodium, Leishmania, Toxoplasma, Cryptosporidium and Eimeria display high conservation in many housekeeping genes, suggesting that these parasites can be attacked by targeting invariant essential proteins. Here, we describe selective and potent inhibition of prolyl-tRNA synthetases (PRSs) from the above parasites using a series of quinazolinone-scaffold compounds. Our PRS-drug co-crystal structures reveal remarkable active site plasticity that accommodates diversely substituted compounds, an enzymatic feature that can be leveraged for refining drug-like properties of quinazolinones on a per parasite basis. A compound we termed In-5 exhibited a unique double conformation, enhanced drug-like properties, and cleared malaria in mice. It thus represents a new lead for optimization. Collectively, our data offer insights into the structure-guided optimization of quinazolinone-based compounds for drug development against multiple human eukaryotic pathogens. Copyright © 2017 Elsevier Ltd. All rights reserved.

Novel approaches for targeting the adenosine A2A receptor.

PubMed

Yuan, Gengyang; Gedeon, Nicholas G; Jankins, Tanner C; Jones, Graham B

2015-01-01

The adenosine A2A receptor (A2AR) represents a drug target for a wide spectrum of diseases. Approaches for targeting this membrane-bound protein have been greatly advanced by new stabilization techniques. The resulting X-ray crystal structures and subsequent analyses provide deep insight to the A2AR from both static and dynamic perspectives. Application of this, along with other biophysical methods combined with fragment-based drug design (FBDD), has become a standard approach in targeting A2AR. Complementarities of in silico screening based- and biophysical screening assisted- FBDD are likely to feature in future approaches in identifying novel ligands against this key receptor. This review describes evolution of the above approaches for targeting A2AR and highlights key modulators identified. It includes a review of: adenosine receptor structures, homology modeling, X-ray structural analysis, rational drug design, biophysical methods, FBDD and in silico screening. As a drug target, the A2AR is attractive as its function plays a role in a wide spectrum of diseases including oncologic, inflammatory, Parkinson's and cardiovascular diseases. Although traditional approaches such as high-throughput screening and homology model-based virtual screening (VS) have played a role in targeting A2AR, numerous shortcomings have generally restricted their applications to specific ligand families. Using stabilization methods for crystallization, X-ray structures of A2AR have greatly accelerated drug discovery and influenced development of biophysical-in silico hybrid screening methods. Application of these new methods to other ARs and G-protein-coupled receptors is anticipated in the future.

Large-scale computational drug repositioning to find treatments for rare diseases.

PubMed

Govindaraj, Rajiv Gandhi; Naderi, Misagh; Singha, Manali; Lemoine, Jeffrey; Brylinski, Michal

2018-01-01

Rare, or orphan, diseases are conditions afflicting a small subset of people in a population. Although these disorders collectively pose significant health care problems, drug companies require government incentives to develop drugs for rare diseases due to extremely limited individual markets. Computer-aided drug repositioning, i.e., finding new indications for existing drugs, is a cheaper and faster alternative to traditional drug discovery offering a promising venue for orphan drug research. Structure-based matching of drug-binding pockets is among the most promising computational techniques to inform drug repositioning. In order to find new targets for known drugs ultimately leading to drug repositioning, we recently developed e MatchSite, a new computer program to compare drug-binding sites. In this study, e MatchSite is combined with virtual screening to systematically explore opportunities to reposition known drugs to proteins associated with rare diseases. The effectiveness of this integrated approach is demonstrated for a kinase inhibitor, which is a confirmed candidate for repositioning to synapsin Ia. The resulting dataset comprises 31,142 putative drug-target complexes linked to 980 orphan diseases. The modeling accuracy is evaluated against the structural data recently released for tyrosine-protein kinase HCK. To illustrate how potential therapeutics for rare diseases can be identified, we discuss a possibility to repurpose a steroidal aromatase inhibitor to treat Niemann-Pick disease type C. Overall, the exhaustive exploration of the drug repositioning space exposes new opportunities to combat orphan diseases with existing drugs. DrugBank/Orphanet repositioning data are freely available to research community at https://osf.io/qdjup/.

Chemoinformatic Analysis of Combinatorial Libraries, Drugs, Natural Products and Molecular Libraries Small Molecule Repository

PubMed Central

Singh, Narender; Guha, Rajarshi; Giulianotti, Marc; Pinilla, Clemencia; Houghten, Richard; Medina-Franco, Jose L.

2009-01-01

A multiple criteria approach is presented, that is used to perform a comparative analysis of four recently developed combinatorial libraries to drugs, Molecular Libraries Small Molecule Repository (MLSMR) and natural products. The compound databases were assessed in terms of physicochemical properties, scaffolds and fingerprints. The approach enables the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity and overall structural novelty. The degree of overlap between combinatorial libraries and drugs was assessed using the R-NN curve methodology, which measures the density of chemical space around a query molecule embedded in the chemical space of a target collection. The combinatorial libraries studied in this work exhibit scaffolds that were not observed in the drug, MLSMR and natural products collections. The fingerprint-based comparisons indicate that these combinatorial libraries are structurally different to current drugs. The R-NN curve methodology revealed that a proportion of molecules in the combinatorial libraries are located within the property space of the drugs. However, the R-NN analysis also showed that there are a significant number of molecules in several combinatorial libraries that are located in sparse regions of the drug space. PMID:19301827

Nanofibers based tissue engineering and drug delivery approaches for myocardial regeneration.

PubMed

Joshi, Jyotsna; Kothapalli, Chandrasekhar R

2015-01-01

Human heart has endogenous regenerative capability; however, the intrinsic repair mechanism is not sufficient to overcome the impact placed by adverse pathological conditions, such as myocardial infarction (MI). In such circumstances, the damaged tissue initiates a series of remodeling process which results in the deterioration of structural, functional, and mechanical properties of the myocardium. To address such adverse conditions, clinical approaches ranging from surgical interventions, pharmaceutical drugs, and device implantation are administered which have played significant role in reducing the mortality rate. However, these approaches do not replace the lost cardiomyocytes, or restore the degraded structure-function relationship of the myocardium. In this aspect, cell-based therapy has gained substantial interest as a potential clinical approach for myocardial regeneration; however this method is impeded by lower graft retention and poor cell viability. To overcome these limitations, biomaterials are being developed as "trojan horses", i.e., vehicles for homing and deploying cells, and as matrices for delivering specific biological, mechanical, and chemical cues intended for tissue regeneration. Similarly, several candidate drugs, potent synthetic and biological molecules, and advanced drug delivery systems are being examined to provide exogenous cues in a controlled fashion to the diseased myocardium. In this article, we review biomaterials-based drug delivery systems for myocardial regeneration, specifically on the applications of hydrogels, microgels, nanoparticles, and nanofibers in the field. The prime focus of the article is on nanofibers-based drug delivery systems that is gaining considerable attention as a biomimetic pharmacological approach. We highlight literature on fabrication methods of self-assembling and electrospun nanofibers, drug incorporation methods and release kinetics, and in vitro and in vivo outcomes from nanofiber-based drug delivery systems in cardiac regeneration.

RFDT: A Rotation Forest-based Predictor for Predicting Drug-Target Interactions Using Drug Structure and Protein Sequence Information.

PubMed

Wang, Lei; You, Zhu-Hong; Chen, Xing; Yan, Xin; Liu, Gang; Zhang, Wei

2018-01-01

Identification of interaction between drugs and target proteins plays an important role in discovering new drug candidates. However, through the experimental method to identify the drug-target interactions remain to be extremely time-consuming, expensive and challenging even nowadays. Therefore, it is urgent to develop new computational methods to predict potential drugtarget interactions (DTI). In this article, a novel computational model is developed for predicting potential drug-target interactions under the theory that each drug-target interaction pair can be represented by the structural properties from drugs and evolutionary information derived from proteins. Specifically, the protein sequences are encoded as Position-Specific Scoring Matrix (PSSM) descriptor which contains information of biological evolutionary and the drug molecules are encoded as fingerprint feature vector which represents the existence of certain functional groups or fragments. Four benchmark datasets involving enzymes, ion channels, GPCRs and nuclear receptors, are independently used for establishing predictive models with Rotation Forest (RF) model. The proposed method achieved the prediction accuracy of 91.3%, 89.1%, 84.1% and 71.1% for four datasets respectively. In order to make our method more persuasive, we compared our classifier with the state-of-theart Support Vector Machine (SVM) classifier. We also compared the proposed method with other excellent methods. Experimental results demonstrate that the proposed method is effective in the prediction of DTI, and can provide assistance for new drug research and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Exploring the associations between drug side-effects and therapeutic indications.

PubMed

Wang, Fei; Zhang, Ping; Cao, Nan; Hu, Jianying; Sorrentino, Robert

2014-10-01

Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical structures or protein targets to predict indications and side-effects. In this study, we compared drug therapeutic indication prediction using various information including chemical structures, protein targets and side-effects. We also compared drug side-effect prediction with various information sources including chemical structures, protein targets and therapeutic indication. Prediction performance based on 10-fold cross-validation demonstrates that drug side-effects and therapeutic indications are the most predictive information source for each other. In addition, we extracted 6706 statistically significant indication-side-effect associations from all known drug-disease and drug-side-effect relationships. We further developed a novel user interface that allows the user to interactively explore these associations in the form of a dynamic bipartitie graph. Many relationship pairs provide explicit repositioning hypotheses (e.g., drugs causing postural hypotension are potential candidates for hypertension) and clear adverse-reaction watch lists (e.g., drugs for heart failure possibly cause impotence). All data sets and highly correlated disease-side-effect relationships are available at http://astro.temple.edu/∼tua87106/druganalysis.html. Copyright © 2014 Elsevier Inc. All rights reserved.

Structure based comprehensive modelling, spatial fingerprints mapping and ADME screening of curcumin analogues as novel ALR2 inhibitors

PubMed Central

Verma, Sant Kumar

2017-01-01

Aldose reductase (ALR2) inhibition is the most legitimate approach for the management of diabetic complications. The limited triumph in the drug development against ALR2 is mainly because of its close structural similarity with the other members of aldo-keto reductase (AKR) superfamily viz. ALR1, AKR1B10; and lipophilicity problem i.e. poor diffusion of synthetic aldose reductase inhibitors (ARIs) to target tissues. The literature evidenced that naturally occurring curcumin demonstrates relatively specific and non-competitive inhibition towards human recombinant ALR2 over ALR1 and AKR1B10; however β-diketone moiety of curcumin is a specific substrate for liver AKRs and accountable for it’s rapid in vivo metabolism. In the present study, structure based comprehensive modelling studies were used to map the pharmacophoric features/spatial fingerprints of curcumin analogues responsible for their ALR2 specificity along with potency on a data set of synthetic curcumin analogues and naturally occurring curcuminoids. The data set molecules were also screened for drug-likeness or ADME parameters, and the screening data strongly support that curcumin analogues could be proposed as a good drug candidate for the development of ALR2 inhibitors with improved pharmacokinetic profile compared to curcuminoids due to the absence of β-diketone moiety in their structural framework. PMID:28399135

Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.

PubMed

Sosa, Ezequiel J; Burguener, Germán; Lanzarotti, Esteban; Defelipe, Lucas; Radusky, Leandro; Pardo, Agustín M; Marti, Marcelo; Turjanski, Adrián G; Fernández Do Porto, Darío

2018-01-04

Available genomic data for pathogens has created new opportunities for drug discovery and development to fight them, including new resistant and multiresistant strains. In particular structural data must be integrated with both, gene information and experimental results. In this sense, there is a lack of an online resource that allows genome wide-based data consolidation from diverse sources together with thorough bioinformatic analysis that allows easy filtering and scoring for fast target selection for drug discovery. Here, we present Target-Pathogen database (http://target.sbg.qb.fcen.uba.ar/patho), designed and developed as an online resource that allows the integration and weighting of protein information such as: function, metabolic role, off-targeting, structural properties including druggability, essentiality and omic experiments, to facilitate the identification and prioritization of candidate drug targets in pathogens. We include in the database 10 genomes of some of the most relevant microorganisms for human health (Mycobacterium tuberculosis, Mycobacterium leprae, Klebsiella pneumoniae, Plasmodium vivax, Toxoplasma gondii, Leishmania major, Wolbachia bancrofti, Trypanosoma brucei, Shigella dysenteriae and Schistosoma Smanosoni) and show its applicability. New genomes can be uploaded upon request. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Probing the structure of Leishmania major DHFR TS and structure based virtual screening of peptide library for the identification of anti-leishmanial leads.

PubMed

Rajasekaran, Rajalakshmi; Chen, Yi-Ping Phoebe

2012-09-01

Leishmaniasis, a multi-faceted ethereal disease is considered to be one of the World's major communicable diseases that demands exhaustive research and control measures. The substantial data on these protozoan parasites has not been utilized completely to develop potential therapeutic strategies against Leishmaniasis. Dihydrofolate reductase thymidylate synthase (DHFR-TS) plays a major role in the infective state of the parasite and hence the DHFR-TS based drugs remains of much interest to researchers working on Leishmaniasis. Although, crystal structures of DHFR-TS from different species including Plasmodium falciparum and Trypanosoma cruzi are available, the experimentally determined structure of the Leishmania major DHFR-TS has not yet been reported in the Protein Data Bank. A high quality three dimensional structure of L.major DHFR-TS has been modeled through the homology modeling approach. Carefully refined and the energy minimized structure of the modeled protein was validated using a number of structure validation programs to confirm its structure quality. The modeled protein structure was used in the process of structure based virtual screening to figure out a potential lead structure against DHFR TS. The lead molecule identified has a binding affinity of 0.51 nM and clearly follows drug like properties.

Protein Translation Enzyme lysyl-tRNA Synthetase Presents a New Target for Drug Development against Causative Agents of Loiasis and Schistosomiasis.

PubMed

Sharma, Arvind; Sharma, Manmohan; Yogavel, Manickam; Sharma, Amit

2016-11-01

Helminth parasites are an assemblage of two major phyla of nematodes (also known as roundworms) and platyhelminths (also called flatworms). These parasites are a major human health burden, and infections caused by helminths are considered under neglected tropical diseases (NTDs). These infections are typified by limited clinical treatment options and threat of drug resistance. Aminoacyl-tRNA synthetases (aaRSs) are vital enzymes that decode genetic information and enable protein translation. The specific inhibition of pathogen aaRSs bores well for development of next generation anti-parasitics. Here, we have identified and annotated aaRSs and accessory proteins from Loa loa (nematode) and Schistosoma mansoni (flatworm) to provide a glimpse of these protein translation enzymes within these parasites. Using purified parasitic lysyl-tRNA synthetases (KRSs), we developed series of assays that address KRS enzymatic activity, oligomeric states, crystal structure and inhibition profiles. We show that L. loa and S. mansoni KRSs are potently inhibited by the fungal metabolite cladosporin. Our co-crystal structure of Loa loa KRS-cladosporin complex reveals key interacting residues and provides a platform for structure-based drug development. This work hence provides a new direction for both novel target discovery and inhibitor development against eukaryotic pathogens that include L. loa and S. mansoni.

Protein Translation Enzyme lysyl-tRNA Synthetase Presents a New Target for Drug Development against Causative Agents of Loiasis and Schistosomiasis

PubMed Central

Yogavel, Manickam; Sharma, Amit

2016-01-01

Helminth parasites are an assemblage of two major phyla of nematodes (also known as roundworms) and platyhelminths (also called flatworms). These parasites are a major human health burden, and infections caused by helminths are considered under neglected tropical diseases (NTDs). These infections are typified by limited clinical treatment options and threat of drug resistance. Aminoacyl-tRNA synthetases (aaRSs) are vital enzymes that decode genetic information and enable protein translation. The specific inhibition of pathogen aaRSs bores well for development of next generation anti-parasitics. Here, we have identified and annotated aaRSs and accessory proteins from Loa loa (nematode) and Schistosoma mansoni (flatworm) to provide a glimpse of these protein translation enzymes within these parasites. Using purified parasitic lysyl-tRNA synthetases (KRSs), we developed series of assays that address KRS enzymatic activity, oligomeric states, crystal structure and inhibition profiles. We show that L. loa and S. mansoni KRSs are potently inhibited by the fungal metabolite cladosporin. Our co-crystal structure of Loa loa KRS-cladosporin complex reveals key interacting residues and provides a platform for structure-based drug development. This work hence provides a new direction for both novel target discovery and inhibitor development against eukaryotic pathogens that include L. loa and S. mansoni. PMID:27806050

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com; Weng, Zuquan; Sun, Liya

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. Inmore » the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.« less

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can freely available at https://github.com/NwpuSY/DT_all.git for academic users. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances

PubMed Central

Lionta, Evanthia; Spyrou, George; Vassilatis, Demetrios K.; Cournia, Zoe

2014-01-01

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

Development of a replicated database of DHCP data for evaluation of drug use.

PubMed Central

Graber, S E; Seneker, J A; Stahl, A A; Franklin, K O; Neel, T E; Miller, R A

1996-01-01

This case report describes development and testing of a method to extract clinical information stored in the Veterans Affairs (VA) Decentralized Hospital Computer System (DHCP) for the purpose of analyzing data about groups of patients. The authors used a microcomputer-based, structured query language (SQL)-compatible, relational database system to replicate a subset of the Nashville VA Hospital's DHCP patient database. This replicated database contained the complete current Nashville DHCP prescription, provider, patient, and drug data sets, and a subset of the laboratory data. A pilot project employed this replicated database to answer questions that might arise in drug-use evaluation, such as identification of cases of polypharmacy, suboptimal drug regimens, and inadequate laboratory monitoring of drug therapy. These database queries included as candidates for review all prescriptions for all outpatients. The queries demonstrated that specific drug-use events could be identified for any time interval represented in the replicated database. PMID:8653451

Development of a replicated database of DHCP data for evaluation of drug use.

PubMed

Graber, S E; Seneker, J A; Stahl, A A; Franklin, K O; Neel, T E; Miller, R A

1996-01-01

This case report describes development and testing of a method to extract clinical information stored in the Veterans Affairs (VA) Decentralized Hospital Computer System (DHCP) for the purpose of analyzing data about groups of patients. The authors used a microcomputer-based, structured query language (SQL)-compatible, relational database system to replicate a subset of the Nashville VA Hospital's DHCP patient database. This replicated database contained the complete current Nashville DHCP prescription, provider, patient, and drug data sets, and a subset of the laboratory data. A pilot project employed this replicated database to answer questions that might arise in drug-use evaluation, such as identification of cases of polypharmacy, suboptimal drug regimens, and inadequate laboratory monitoring of drug therapy. These database queries included as candidates for review all prescriptions for all outpatients. The queries demonstrated that specific drug-use events could be identified for any time interval represented in the replicated database.

Intrinsic flexibility of West Nile virus protease in solution characterized using small-angle X-ray scattering.

PubMed

Garces, Andrea P; Watowich, Stanley J

2013-10-01

West Nile virus (WNV) is a mosquito-borne flavivirus with a rapidly expanding global distribution. Infection can cause severe neurological disease and fatality in humans. Efforts are ongoing to develop antiviral drugs that inhibit the WNV protease, a viral enzyme required for polyprotein processing. Unfortunately, little is known about the solution structure of recombinant WNV protease (NS2B-NS3pro) used for antiviral drug discovery and development, although X-ray crystal structures and nuclear magnetic resonance (NMR) studies have provided valuable insights into the interactions between NS2B-NS3pro and peptide-based inhibitors. We completed small-angle X-ray scattering and Fourier transform infrared spectroscopy experiments to determine the solution structure and dynamics of WNV NS2B-NS3pro in the absence of a bound substrate or inhibitor. Importantly, these solution studies suggested that all or most of the NS2B cofactor was highly flexible and formed an ensemble of structures, in contrast to the NS2B tertiary structures observed in crystallographic and NMR studies. The secondary structure of NS2B-NS3pro in solution had high β-content, similar to the secondary structure observed in crystallographic studies. This work provided evidence of the intrinsic flexibility and conformational heterogeneity of the NS2B chain of the WNV protease in the absence of substratelike ligands, which should be considered during antiviral drug discovery and development efforts.

New Scaffold for Angiogenesis Inhibitors Discovered by Targeted Chemical Transformations of Wondonin Natural Products.

PubMed

Yu, Shuai; Oh, Jedo; Li, Feng; Kwon, Yongseok; Cho, Hyunkyung; Shin, Jongheon; Lee, Sang Kook; Kim, Sanghee

2017-10-12

The structure of wondonin marine natural products was renovated to attain new drug-like scaffolds. Wondonins have novel antiangiogenic properties without overt cytotoxicity. However, the chemical instability and synthetic complexity of wondonins have hindered their development as a new type of antiangiogenesis agent. Using a structure-based bioisosterism, the benzodioxole moiety was changed to benzothiazole, and the imidazole moiety was replaced by 1,2,3-triazole. Our efforts resulted in a new scaffold with enhanced antiangiogenic activity and minimized cytotoxicity. One compound with this scaffold effectively inhibited hyaloid vessel formation in diabetic retinopathy mimic zebrafish model. The biological findings together suggested the potential of the scaffold as a lead structure for development of antiangiogenic drugs with novel functions and as a probe to elucidate new biological mechanisms associated with angiogenesis.

NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

PubMed Central

Chen, Ming; Wang, Quanxin; Zhang, Lixin; Yan, Guiying

2016-01-01

Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations. PMID:27415801

Facilitating adverse drug event detection in pharmacovigilance databases using molecular structure similarity: application to rhabdomyolysis

PubMed Central

Vilar, Santiago; Harpaz, Rave; Chase, Herbert S; Costanzi, Stefano; Rabadan, Raul

2011-01-01

Background Adverse drug events (ADE) cause considerable harm to patients, and consequently their detection is critical for patient safety. The US Food and Drug Administration maintains an adverse event reporting system (AERS) to facilitate the detection of ADE in drugs. Various data mining approaches have been developed that use AERS to detect signals identifying associations between drugs and ADE. The signals must then be monitored further by domain experts, which is a time-consuming task. Objective To develop a new methodology that combines existing data mining algorithms with chemical information by analysis of molecular fingerprints to enhance initial ADE signals generated from AERS, and to provide a decision support mechanism to facilitate the identification of novel adverse events. Results The method achieved a significant improvement in precision in identifying known ADE, and a more than twofold signal enhancement when applied to the ADE rhabdomyolysis. The simplicity of the method assists in highlighting the etiology of the ADE by identifying structurally similar drugs. A set of drugs with strong evidence from both AERS and molecular fingerprint-based modeling is constructed for further analysis. Conclusion The results demonstrate that the proposed methodology could be used as a pharmacovigilance decision support tool to facilitate ADE detection. PMID:21946238

Critical considerations for developing nucleic acid macromolecule based drug products.

PubMed

Muralidhara, Bilikallahalli K; Baid, Rinku; Bishop, Steve M; Huang, Min; Wang, Wei; Nema, Sandeep

2016-03-01

Protein expression therapy using nucleic acid macromolecules (NAMs) as a new paradigm in medicine has recently gained immense therapeutic potential. With the advancement of nonviral delivery it has been possible to target NAMs against cancer, immunodeficiency and infectious diseases. Owing to the complex and fragile structure of NAMs, however, development of a suitable, stable formulation for a reasonable product shelf-life and efficacious delivery is indeed challenging to achieve. This review provides a synopsis of challenges in the formulation and stability of DNA/m-RNA based medicines and probable mitigation strategies including a brief summary of delivery options to the target cells. Nucleic acid based drugs at various stages of ongoing clinical trials are compiled. Copyright © 2016. Published by Elsevier Ltd.

Generating "fragment-based virtual library" using pocket similarity search of ligand-receptor complexes.

PubMed

Khashan, Raed S

2015-01-01

As the number of available ligand-receptor complexes is increasing, researchers are becoming more dedicated to mine these complexes to aid in the drug design and development process. We present free software which is developed as a tool for performing similarity search across ligand-receptor complexes for identifying binding pockets which are similar to that of a target receptor. The search is based on 3D-geometric and chemical similarity of the atoms forming the binding pocket. For each match identified, the ligand's fragment(s) corresponding to that binding pocket are extracted, thus forming a virtual library of fragments (FragVLib) that is useful for structure-based drug design. The program provides a very useful tool to explore available databases.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

PubMed Central

Basith, Shaherin; Cui, Minghua; Macalino, Stephani J. Y.; Park, Jongmi; Clavio, Nina A. B.; Kang, Soosung; Choi, Sun

2018-01-01

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the “golden age for GPCR structural biology.” Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand– and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed. PMID:29593527

An integrated structure- and system-based framework to identify new targets of metabolites and known drugs

PubMed Central

Naveed, Hammad; Hameed, Umar S.; Harrus, Deborah; Bourguet, William; Arold, Stefan T.; Gao, Xin

2015-01-01

Motivation: The inherent promiscuity of small molecules towards protein targets impedes our understanding of healthy versus diseased metabolism. This promiscuity also poses a challenge for the pharmaceutical industry as identifying all protein targets is important to assess (side) effects and repositioning opportunities for a drug. Results: Here, we present a novel integrated structure- and system-based approach of drug-target prediction (iDTP) to enable the large-scale discovery of new targets for small molecules, such as pharmaceutical drugs, co-factors and metabolites (collectively called ‘drugs’). For a given drug, our method uses sequence order–independent structure alignment, hierarchical clustering and probabilistic sequence similarity to construct a probabilistic pocket ensemble (PPE) that captures promiscuous structural features of different binding sites on known targets. A drug’s PPE is combined with an approximation of its delivery profile to reduce false positives. In our cross-validation study, we use iDTP to predict the known targets of 11 drugs, with 63% sensitivity and 81% specificity. We then predicted novel targets for these drugs—two that are of high pharmacological interest, the peroxisome proliferator-activated receptor gamma and the oncogene B-cell lymphoma 2, were successfully validated through in vitro binding experiments. Our method is broadly applicable for the prediction of protein-small molecule interactions with several novel applications to biological research and drug development. Availability and implementation: The program, datasets and results are freely available to academic users at http://sfb.kaust.edu.sa/Pages/Software.aspx. Contact: xin.gao@kaust.edu.sa and stefan.arold@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26286808

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

PubMed

Cao, Han; Ng, Marcus C K; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W I

2017-09-01

[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

NASA Astrophysics Data System (ADS)

Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

2017-09-01

α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM. Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

GalaxyGPCRloop: Template-Based and Ab Initio Structure Sampling of the Extracellular Loops of G-Protein-Coupled Receptors.

PubMed

Won, Jonghun; Lee, Gyu Rie; Park, Hahnbeom; Seok, Chaok

2018-06-07

The second extracellular loops (ECL2s) of G-protein-coupled receptors (GPCRs) are often involved in GPCR functions, and their structures have important implications in drug discovery. However, structure prediction of ECL2 is difficult because of its long length and the structural diversity among different GPCRs. In this study, a new ECL2 conformational sampling method involving both template-based and ab initio sampling was developed. Inspired by the observation of similar ECL2 structures of closely related GPCRs, a template-based sampling method employing loop structure templates selected from the structure database was developed. A new metric for evaluating similarity of the target loop to templates was introduced for template selection. An ab initio loop sampling method was also developed to treat cases without highly similar templates. The ab initio method is based on the previously developed fragment assembly and loop closure method. A new sampling component that takes advantage of secondary structure prediction was added. In addition, a conserved disulfide bridge restraining ECL2 conformation was predicted and analytically incorporated into sampling, reducing the effective dimension of the conformational search space. The sampling method was combined with an existing energy function for comparison with previously reported loop structure prediction methods, and the benchmark test demonstrated outstanding performance.

Fabrication of Hyperbranched Block-Statistical Copolymer-Based Prodrug with Dual Sensitivities for Controlled Release.

PubMed

Zheng, Luping; Wang, Yunfei; Zhang, Xianshuo; Ma, Liwei; Wang, Baoyan; Ji, Xiangling; Wei, Hua

2018-01-17

Dendrimer with hyperbranched structure and multivalent surface is regarded as one of the most promising candidates close to the ideal drug delivery systems, but the clinical translation and scale-up production of dendrimer has been hampered significantly by the synthetic difficulties. Therefore, there is considerable scope for the development of novel hyperbranched polymer that can not only address the drawbacks of dendrimer but maintain its advantages. The reversible addition-fragmentation chain transfer self-condensing vinyl polymerization (RAFT-SCVP) technique has enabled facile preparation of segmented hyperbranched polymer (SHP) by using chain transfer monomer (CTM)-based double-head agent during the past decade. Meanwhile, the design and development of block-statistical copolymers has been proven in our recent studies to be a simple yet effective way to address the extracellular stability vs intracellular high delivery efficacy dilemma. To integrate the advantages of both hyperbranched and block-statistical structures, we herein reported the fabrication of hyperbranched block-statistical copolymer-based prodrug with pH and reduction dual sensitivities using RAFT-SCVP and post-polymerization click coupling. The external homo oligo(ethylene glycol methyl ether methacrylate) (OEGMA) block provides sufficient extracellularly colloidal stability for the nanocarriers by steric hindrance, and the interior OEGMA units incorporated by the statistical copolymerization promote intracellular drug release by facilitating the permeation of GSH and H + for the cleavage of the reduction-responsive disulfide bond and pH-liable carbonate link as well as weakening the hydrophobic encapsulation of drug molecules. The delivery efficacy of the target hyperbranched block-statistical copolymer-based prodrug was evaluated in terms of in vitro drug release and cytotoxicity studies, which confirms both acidic pH and reduction-triggered drug release for inhibiting proliferation of HeLa cells. Interestingly, the simultaneous application of both acidic pH and GSH triggers promoted significantly the cleavage and release of CPT compared to the exertion of single trigger. This study thus developed a facile approach toward hyperbranched polymer-based prodrugs with high therapeutic efficacy for anticancer drug delivery.

Insight into drug resistance mechanisms and discovery of potential inhibitors against wild-type and L1196M mutant ALK from FDA-approved drugs.

PubMed

Li, Jianzong; Liu, Wei; Luo, Hao; Bao, Jinku

2016-09-01

Anaplastic lymphoma kinase (ALK) plays a crucial role in multiple malignant cancers. It is known as a well-established target for the treatment of ALK-dependent cancers. Even though substantial efforts have been made to develop ALK inhibitors, only crizotinib, ceritinib, and alectinib had been approved by the U.S. Food and Drug Administration for patients with ALK-positive non-small cell lung cancer (NSCLC). The secondary mutations with drug-resistance bring up difficulties to develop effective drugs for ALK-positive cancers. To give a comprehensive understanding of molecular mechanism underlying inhibitor response to ALK tyrosine kinase mutations, we established an accurate assessment for the extensive profile of drug against ALK mutations by means of computational approaches. The molecular mechanics-generalized Born surface area (MM-GBSA) method based on molecular dynamics (MD) simulation was carried out to calculate relative binding free energies for receptor-drug systems. In addition, the structure-based virtual screening was utilized to screen effective inhibitors targeting wild-type ALK and the gatekeeper mutation L1196M from 3180 approved drugs. Finally, the mechanism of drug resistance was discussed, several novel potential wild-type and L1196M mutant ALK inhibitors were successfully identified.

Chemistry and Biology of the Caged Garcinia Xanthones

PubMed Central

Chantarasriwong, Oraphin; Batova, Ayse; Chavasiri, Warinthorn

2011-01-01

Natural products have been a great source of many small molecule drugs for various diseases. In spite of recent advances in biochemical engineering and fermentation technologies that allow us to explore microorganisms and the marine environment as alternative sources of drugs, more than 70% of the current small molecule therapeutics derive their structures from plants used in traditional medicine. Natural-product-based drug discovery relies heavily on advances made in the sciences of biology and chemistry. Whereas biology aims to investigate the mode of action of a natural product, chemistry aims to overcome challenges related to its supply, bioactivity, and target selectivity. This review summarizes the explorations of the caged Garcinia xanthones, a family of plant metabolites that possess a unique chemical structure, potent bioactivities, and a promising pharmacology for drug design and development. PMID:20648491

Prediction of drug indications based on chemical interactions and chemical similarities.

PubMed

Huang, Guohua; Lu, Yin; Lu, Changhong; Zheng, Mingyue; Cai, Yu-Dong

2015-01-01

Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs.

Prediction of Drug Indications Based on Chemical Interactions and Chemical Similarities

PubMed Central

Huang, Guohua; Lu, Yin; Lu, Changhong; Cai, Yu-Dong

2015-01-01

Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs. PMID:25821813

Novel approaches to anticonvulsant drug discovery.

PubMed

Miziak, Barbara; Chrościńska-Krawczyk, Magdalena; Błaszczyk, Barbara; Radzik, Iwona; Czuczwar, Stanisław J

2013-11-01

The history of epilepsy dates back to 2000 BC. Yet, it was not until 1912 that the activity of the first antiepileptic, phenobarbital was discovered by accident. After this discovery, the next antiepileptic drugs to be discovered (phenytoin and primidone) were based on the phenobarbital's structure. Then, in 1960, carbamazepine was developed empirically, while in 1962, valproate demonstrated anticonvulsant activity against experimental seizures. The next antiepileptic drugs synthesized were either modifications of the existing drugs (such as oxcarbazepine and pregabalin) or completely novel chemical structures (lacosamide, perampanel and retigabine). The present paper briefly refers to the history of epilepsy and development of antiepileptic drugs. Further, the paper provides a discussion on the antiepileptogenic effects of antiepileptic drugs in terms of the constant percentage of epileptic patients with refractory seizures. The authors also review the likely factors involved in the false refractoriness (such as through the use of caffeine-containing beverages and smoking). Finally, the authors consider future directions in the search of novel antiepileptic drugs. In spite of the considerable number of newer antiepileptic drugs, the number of drug-resistant epileptic patients remains unchanged. This may be rather an indication of the suitability of the currently available discovery procedures for effective antiepileptic drugs in the whole population of epileptic patients. The authors, however, believe that it is likely that models of mimic chronic epilepsy will help bridge the gaps and aid in the discovery of novel antiepileptic drugs - ones that can effectively modify the course of the disease.

TIPdb: a database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan.

PubMed

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs.

TIPdb: A Database of Anticancer, Antiplatelet, and Antituberculosis Phytochemicals from Indigenous Plants in Taiwan

PubMed Central

Lin, Ying-Chi; Wang, Chia-Chi; Chen, Ih-Sheng; Jheng, Jhao-Liang; Li, Jih-Heng; Tung, Chun-Wei

2013-01-01

The unique geographic features of Taiwan are attributed to the rich indigenous and endemic plant species in Taiwan. These plants serve as resourceful bank for biologically active phytochemicals. Given that these plant-derived chemicals are prototypes of potential drugs for diseases, databases connecting the chemical structures and pharmacological activities may facilitate drug development. To enhance the utility of the data, it is desirable to develop a database of chemical compounds and corresponding activities from indigenous plants in Taiwan. A database of anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan was constructed. The database, TIPdb, is composed of a standardized format of published anticancer, antiplatelet, and antituberculosis phytochemicals from indigenous plants in Taiwan. A browse function was implemented for users to browse the database in a taxonomy-based manner. Search functions can be utilized to filter records of interest by botanical name, part, chemical class, or compound name. The structured and searchable database TIPdb was constructed to serve as a comprehensive and standardized resource for anticancer, antiplatelet, and antituberculosis compounds search. The manually curated chemical structures and activities provide a great opportunity to develop quantitative structure-activity relationship models for the high-throughput screening of potential anticancer, antiplatelet, and antituberculosis drugs. PMID:23766708

Design of study without drugs--a Surinamese school-based drug-prevention program for adolescents.

PubMed

Ishaak, Fariel; de Vries, Nanne Karel; van der Wolf, Kees

2015-10-12

The aim of this study was to design the content and accompanying materials for a school-based program--Study without Drugs--for adolescents in junior secondary schools in Suriname based on the starting points and tasks of the fourth step of the Intervention Mapping protocol (which consists of six steps). A program based on this protocol should include a combination of theory, empirical evidence, and qualitative and quantitative research. Two surveys were conducted when designing the program. In Survey I, teachers and students were asked to complete a questionnaire to determine which school year they thought would be most appropriate for implementing a drug-prevention program for adolescents (we completed a similar survey as part of previous research). An attempt was made to identify suitable culturally sensitive elements to include in the program. In Survey II, the same teachers were asked to complete a questionnaire to determine the programs' scope, sequence, structure, and topics as well as the general didactic principles to serve as a basis for program design. After outlining the program plan, lessons, and materials, we conducted a formative pretest evaluation among teachers, students, and parents. That evaluation included measures related to the program's attractiveness, comprehensibility, and usefulness. The resulting lessons were presented to the teachers for assessment. The drug-prevention program we developed comprises 10 activities and lasts 2-2.5 months in an actual school setting. The activities take place during Dutch, biology, physical education, art, religion, and social studies lessons. We based the structure of the lessons in the program on McGuire's Persuasion Communication Model, which takes into account important didactic principles. Evaluations of the program materials and lesson plans by students, teachers, and parents were mostly positive. We believe that using the fourth step of the Intervention Mapping protocol to develop a drug-prevention intervention for adolescents has a produced promising, feasible program.

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist

NASA Astrophysics Data System (ADS)

Singh, Nidhi; Chevé, Gwénaël; Ferguson, David M.; McCurdy, Christopher R.

2006-08-01

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based "agonist-bound" hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental p K i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.

Structural and Thermodynamic Properties of Amyloid-β Peptides: Impact of Fragment Size

NASA Astrophysics Data System (ADS)

Kitahara, T.; Wise-Scira, O.; Coskuner, O.

2010-10-01

Alzheimer's disease is a progressive neurodegenerative disease whose physiological characteristics include the accumulation of amyloid-containing deposits in the brain and consequent synapse and neuron loss. Unfortunately, most widely used drugs for the treatment can palliate the outer symptoms but cannot cure the disease itself. Hence, developing a new drug that can cure it. Most recently, the ``early aggregation and monomer'' hypothesis has become popular and a few drugs have been developed based on this hypothesis. Detailed understanding of the amyloid-β peptide structure can better help us to determine more effective treatment strategies; indeed, the structure of Amyloid has been studied extensively employing experimental and theoretical tools. Nevertheless, those studies have employed different fragment sizes of Amyloid and characterized its conformational nature in different media. Thus, the structural properties might be different from each other and provide a reason for the existing debates in the literature. Here, we performed all-atom MD simulations and present the structural and thermodynamic properties of Aβ1-16, Aβ1-28, and Aβ1-42 in the gas phase and in aqueous solution. Our studies show that the overall structures, secondary structures, and the calculated thermodynamic properties change with increasing peptide size. In addition, we find that the structural properties of those peptides are different from each other in the gas phase and in aqueous solution.

CANDO and the infinite drug discovery frontier

PubMed Central

Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram

2014-01-01

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

Development of a SNOMED CT based national medication decision support system.

PubMed

Greibe, Kell

2013-01-01

Physicians often lack the time to familiarize themselves with the details of particular allergies or other drug restrictions. Clinical Decision Support (CDS), based on a structured terminology as SNOMED CT (SCT), can help physicians get an overview, by automatically alerting allergy, interactions and other important information. The centralized CDS platform based on SCT, controls Allergy, Interactions, Risk Situation Drugs and Max Dose restrictions by the help of databases developed for these specific purposes. The CDS will respond to automatic web service requests from the hospital or GP electronic medication system (EMS) during prescription, and return alerts and information. The CDS also contains a Physicians Preference Database where the physicians individually can set which kind of alerts they want to see. The result is clinically useful information physicians can use as a base for a more effective and safer treatment, without developing alert fatigue.

Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones.

PubMed

Martins Alho, Miriam A; Marrero-Ponce, Yovani; Barigye, Stephen J; Meneses-Marcel, Alfredo; Machado Tugores, Yanetsy; Montero-Torres, Alina; Gómez-Barrio, Alicia; Nogal, Juan J; García-Sánchez, Rory N; Vega, María Celeste; Rolón, Miriam; Martínez-Fernández, Antonio R; Escario, José A; Pérez-Giménez, Facundo; Garcia-Domenech, Ramón; Rivera, Norma; Mondragón, Ricardo; Mondragón, Mónica; Ibarra-Velarde, Froylán; Lopez-Arencibia, Atteneri; Martín-Navarro, Carmen; Lorenzo-Morales, Jacob; Cabrera-Serra, Maria Gabriela; Piñero, Jose; Tytgat, Jan; Chicharro, Roberto; Arán, Vicente J

2014-03-01

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In an effort to overcome this problem, the main purpose of this study is to develop a QSARs-based ensemble classifier for antiprotozoan drug-like entities from a heterogeneous compounds collection. Here, we use some of the TOMOCOMD-CARDD molecular descriptors and linear discriminant analysis (LDA) to derive individual linear classification functions in order to discriminate between antiprotozoan and non-antiprotozoan compounds as a way to enable the computational screening of virtual combinatorial datasets and/or drugs already approved. Firstly, we construct a wide-spectrum benchmark database comprising of 680 organic chemicals with great structural variability (254 of them antiprotozoan agents and 426 to drugs having other clinical uses). This series of compounds was processed by a k-means cluster analysis in order to design training and predicting sets. In total, seven discriminant functions were obtained, by using the whole set of atom-based linear indices. All the LDA-based QSAR models show accuracies above 85% in the training set and values of Matthews correlation coefficients (C) vary from 0.70 to 0.86. The external validation set shows rather-good global classifications of around 80% (92.05% for best equation). Later, we developed a multi-agent QSAR classification system, in which the individual QSAR outputs are the inputs of the aforementioned fusion approach. Finally, the fusion model was used for the identification of a novel generation of lead-like antiprotozoan compounds by using ligand-based virtual screening of 'available' small molecules (with synthetic feasibility) in our 'in-house' library. A new molecular subsystem (quinoxalinones) was then theoretically selected as a promising lead series, and its derivatives subsequently synthesized, structurally characterized, and experimentally assayed by using in vitro screening that took into consideration a battery of five parasite-based assays. The chemicals 11(12) and 16 are the most active (hits) against apicomplexa (sporozoa) and mastigophora (flagellata) subphylum parasites, respectively. Both compounds depicted good activity in every protozoan in vitro panel and they did not show unspecific cytotoxicity on the host cells. The described technical framework seems to be a promising QSAR-classifier tool for the molecular discovery and development of novel classes of broad-antiprotozoan-spectrum drugs, which may meet the dual challenges posed by drug-resistant parasites and the rapid progression of protozoan illnesses. Copyright © 2014 Elsevier Ltd. All rights reserved.

From Medicinal Chemistry to Human Health: Current Approaches to Drug Discovery for Cancer and Neglected Tropical Diseases.

PubMed

Ferreira, Leonardo G; Oliva, Glaucius; Andricopulo, Adriano D

2018-01-01

Scientific and technological breakthroughs have compelled the current players in drug discovery to increasingly incorporate knowledge-based approaches. This evolving paradigm, which has its roots attached to the recent advances in medicinal chemistry, molecular and structural biology, has unprecedentedly demanded the development of up-to-date computational approaches, such as bio- and chemo-informatics. These tools have been pivotal to catalyzing the ever-increasing amount of data generated by the molecular sciences, and to converting the data into insightful guidelines for use in the research pipeline. As a result, ligand- and structure-based drug design have emerged as key pathways to address the pharmaceutical industry's striking demands for innovation. These approaches depend on a keen integration of experimental and molecular modeling methods to surmount the main challenges faced by drug candidates - in vivo efficacy, pharmacodynamics, metabolism, pharmacokinetics and safety. To that end, the Laboratório de Química Medicinal e Computacional (LQMC) of the Universidade de São Paulo has developed forefront research on highly prevalent and life-threatening neglected tropical diseases and cancer. By taking part in global initiatives for pharmaceutical innovation, the laboratory has contributed to the advance of these critical therapeutic areas through the use of cutting-edge strategies in medicinal chemistry.

ACFIS: a web server for fragment-based drug discovery

PubMed Central

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-01-01

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown ‘chemical space’ to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for ‘chemical space’, which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. PMID:27150808

ACFIS: a web server for fragment-based drug discovery.

PubMed

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-07-08

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Fragment-based virtual screening approach and molecular dynamics simulation studies for identification of BACE1 inhibitor leads.

PubMed

Manoharan, Prabu; Ghoshal, Nanda

2018-05-01

Traditional structure-based virtual screening method to identify drug-like small molecules for BACE1 is so far unsuccessful. Location of BACE1, poor Blood Brain Barrier permeability and P-glycoprotein (Pgp) susceptibility of the inhibitors make it even more difficult. Fragment-based drug design method is suitable for efficient optimization of initial hit molecules for target like BACE1. We have developed a fragment-based virtual screening approach to identify/optimize the fragment molecules as a starting point. This method combines the shape, electrostatic, and pharmacophoric features of known fragment molecules, bound to protein conjugate crystal structure, and aims to identify both chemically and energetically feasible small fragment ligands that bind to BACE1 active site. The two top-ranked fragment hits were subjected for a 53 ns MD simulation. Principle component analysis and free energy landscape analysis reveal that the new ligands show the characteristic features of established BACE1 inhibitors. The potent method employed in this study may serve for the development of potential lead molecules for BACE1-directed Alzheimer's disease therapeutics.

Carbon-based hybrid nanogels: a synergistic nanoplatform for combined biosensing, bioimaging, and responsive drug delivery.

PubMed

Wang, Hui; Chen, Qianwang; Zhou, Shuiqin

2018-06-05

Nanosized crosslinked polymer networks, named as nanogels, are playing an increasingly important role in a diverse range of applications by virtue of their porous structures, large surface area, good biocompatibility and responsiveness to internal and/or external chemico-physical stimuli. Recently, a variety of carbon nanomaterials, such as carbon quantum dots, graphene/graphene oxide nanosheets, fullerenes, carbon nanotubes, and nanodiamonds, have been embedded into responsive polymer nanogels, in order to integrate the unique electro-optical properties of carbon nanomaterials with the merits of nanogels into a single hybrid nanogel system for improvement of their applications in nanomedicine. A vast number of studies have been pursued to explore the applications of carbon-based hybrid nanogels in biomedical areas for biosensing, bioimaging, and smart drug carriers with combinatorial therapies and/or theranostic ability. New synthetic methods and structures have been developed to prepare carbon-based hybrid nanogels with versatile properties and functions. In this review, we summarize the latest developments and applications and address the future perspectives of these carbon-based hybrid nanogels in the biomedical field.

Structural analyses of Candida albicans sterol 14α-demethylase complexed with azole drugs address the molecular basis of azole-mediated inhibition of fungal sterol biosynthesis

PubMed Central

Hargrove, Tatiana Y.; Friggeri, Laura; Wawrzak, Zdzislaw; Qi, Aidong; Hoekstra, William J.; Schotzinger, Robert J.; York, John D.; Guengerich, F. Peter; Lepesheva, Galina I.

2017-01-01

With some advances in modern medicine (such as cancer chemotherapy, broad exposure to antibiotics, and immunosuppression), the incidence of opportunistic fungal pathogens such as Candida albicans has increased. Cases of drug resistance among these pathogens have become more frequent, requiring the development of new drugs and a better understanding of the targeted enzymes. Sterol 14α-demethylase (CYP51) is a cytochrome P450 enzyme required for biosynthesis of sterols in eukaryotic cells and is the major target of clinical drugs for managing fungal pathogens, but some of the CYP51 key features important for rational drug design have remained obscure. We report the catalytic properties, ligand-binding profiles, and inhibition of enzymatic activity of C. albicans CYP51 by clinical antifungal drugs that are used systemically (fluconazole, voriconazole, ketoconazole, itraconazole, and posaconazole) and topically (miconazole and clotrimazole) and by a tetrazole-based drug candidate, VT-1161 (oteseconazole: (R)-2-(2,4-difluorophenyl)-1,1-difluoro-3-(1H-tetrazol-1-yl)-1-(5-(4-(2,2,2-trifluoroethoxy)phenyl)pyridin-2-yl)propan-2-ol). Among the compounds tested, the first-line drug fluconazole was the weakest inhibitor, whereas posaconazole and VT-1161 were the strongest CYP51 inhibitors. We determined the X-ray structures of C. albicans CYP51 complexes with posaconazole and VT-1161, providing a molecular mechanism for the potencies of these drugs, including the activity of VT-1161 against Candida krusei and Candida glabrata, pathogens that are intrinsically resistant to fluconazole. Our comparative structural analysis outlines phylum-specific CYP51 features that could direct future rational development of more efficient broad-spectrum antifungals. PMID:28258218

Structural analyses of Candida albicans sterol 14α-demethylase complexed with azole drugs address the molecular basis of azole-mediated inhibition of fungal sterol biosynthesis.

PubMed

Hargrove, Tatiana Y; Friggeri, Laura; Wawrzak, Zdzislaw; Qi, Aidong; Hoekstra, William J; Schotzinger, Robert J; York, John D; Guengerich, F Peter; Lepesheva, Galina I

2017-04-21

With some advances in modern medicine (such as cancer chemotherapy, broad exposure to antibiotics, and immunosuppression), the incidence of opportunistic fungal pathogens such as Candida albicans has increased. Cases of drug resistance among these pathogens have become more frequent, requiring the development of new drugs and a better understanding of the targeted enzymes. Sterol 14α-demethylase (CYP51) is a cytochrome P450 enzyme required for biosynthesis of sterols in eukaryotic cells and is the major target of clinical drugs for managing fungal pathogens, but some of the CYP51 key features important for rational drug design have remained obscure. We report the catalytic properties, ligand-binding profiles, and inhibition of enzymatic activity of C. albicans CYP51 by clinical antifungal drugs that are used systemically (fluconazole, voriconazole, ketoconazole, itraconazole, and posaconazole) and topically (miconazole and clotrimazole) and by a tetrazole-based drug candidate, VT-1161 (oteseconazole: ( R )-2-(2,4-difluorophenyl)-1,1-difluoro-3-(1 H -tetrazol-1-yl)-1-(5-(4-(2,2,2-trifluoroethoxy)phenyl)pyridin-2-yl)propan-2-ol). Among the compounds tested, the first-line drug fluconazole was the weakest inhibitor, whereas posaconazole and VT-1161 were the strongest CYP51 inhibitors. We determined the X-ray structures of C. albicans CYP51 complexes with posaconazole and VT-1161, providing a molecular mechanism for the potencies of these drugs, including the activity of VT-1161 against Candida krusei and Candida glabrata , pathogens that are intrinsically resistant to fluconazole. Our comparative structural analysis outlines phylum-specific CYP51 features that could direct future rational development of more efficient broad-spectrum antifungals. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

HPMA Copolymer-Drug Conjugates with Controlled Tumor-Specific Drug Release.

PubMed

Chytil, Petr; Koziolová, Eva; Etrych, Tomáš; Ulbrich, Karel

2018-01-01

Over the past few decades, numerous polymer drug carrier systems are designed and synthesized, and their properties are evaluated. Many of these systems are based on water-soluble polymer carriers of low-molecular-weight drugs and compounds, e.g., cytostatic agents, anti-inflammatory drugs, or multidrug resistance inhibitors, all covalently bound to a carrier by a biodegradable spacer that enables controlled release of the active molecule to achieve the desired pharmacological effect. Among others, the synthetic polymer carriers based on N-(2-hydroxypropyl) methacrylamide (HPMA) copolymers are some of the most promising carriers for this purpose. This review focuses on advances in the development of HPMA copolymer carriers and their conjugates with anticancer drugs, with triggered drug activation in tumor tissue and especially in tumor cells. Specifically, this review highlights the improvements in polymer drug carrier design with respect to the structure of a spacer to influence controlled drug release and activation, and its impact on the drug pharmacokinetics, enhanced tumor uptake, cellular trafficking, and in vivo antitumor activity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Similarity-based modeling in large-scale prediction of drug-drug interactions.

PubMed

Vilar, Santiago; Uriarte, Eugenio; Santana, Lourdes; Lorberbaum, Tal; Hripcsak, George; Friedman, Carol; Tatonetti, Nicholas P

2014-09-01

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.

[Pharmacological differences between inhibitor drugs of the renin-angiotensin aldosterone system].

PubMed

Méndez-Durán, Antonio

2011-01-01

The activation of the renin-angiotensin-aldosterone cascade is a mechanism that generates high blood pressure. The structure has been identified and can be blocked through specific enzymatic pathways or receptors. We have a diversity of medications that act on this system. It is useful to develop the skill in clinical practice for selecting a drug from a wide variety. Renin-angiotensin system inhibitors share many pharmacological and pharmacokinetic characteristics but not all them are equivalent. Knowledge based on scientific evidence allows the clinician to choose the ideal drug for each patient.

Molecular dynamics studies of a hexameric purine nucleoside phosphorylase.

PubMed

Zanchi, Fernando Berton; Caceres, Rafael Andrade; Stabeli, Rodrigo Guerino; de Azevedo, Walter Filgueira

2010-03-01

Purine nucleoside phosphorylase (PNP) (EC.2.4.2.1) is an enzyme that catalyzes the cleavage of N-ribosidic bonds of the purine ribonucleosides and 2-deoxyribonucleosides in the presence of inorganic orthophosphate as a second substrate. This enzyme is involved in purine-salvage pathway and has been proposed as a promising target for design and development of antimalarial and antibacterial drugs. Recent elucidation of the three-dimensional structure of PNP by X-ray protein crystallography left open the possibility of structure-based virtual screening initiatives in combination with molecular dynamics simulations focused on identification of potential new antimalarial drugs. Most of the previously published molecular dynamics simulations of PNP were carried out on human PNP, a trimeric PNP. The present article describes for the first time molecular dynamics simulations of hexameric PNP from Plasmodium falciparum (PfPNP). Two systems were simulated in the present work, PfPNP in ligand free form, and in complex with immucillin and sulfate. Based on the dynamical behavior of both systems the main results related to structural stability and protein-drug interactions are discussed.

Consensus Recommendations for Systematic Evaluation of Drug-Drug Interaction Evidence for Clinical Decision Support

PubMed Central

Scheife, Richard T.; Hines, Lisa E.; Boyce, Richard D.; Chung, Sophie P.; Momper, Jeremiah; Sommer, Christine D.; Abernethy, Darrell R.; Horn, John; Sklar, Stephen J.; Wong, Samantha K.; Jones, Gretchen; Brown, Mary; Grizzle, Amy J.; Comes, Susan; Wilkins, Tricia Lee; Borst, Clarissa; Wittie, Michael A.; Rich, Alissa; Malone, Daniel C.

2015-01-01

Background Healthcare organizations, compendia, and drug knowledgebase vendors use varying methods to evaluate and synthesize evidence on drug-drug interactions (DDIs). This situation has a negative effect on electronic prescribing and medication information systems that warn clinicians of potentially harmful medication combinations. Objective To provide recommendations for systematic evaluation of evidence from the scientific literature, drug product labeling, and regulatory documents with respect to DDIs for clinical decision support. Methods A conference series was conducted to develop a structured process to improve the quality of DDI alerting systems. Three expert workgroups were assembled to address the goals of the conference. The Evidence Workgroup consisted of 15 individuals with expertise in pharmacology, drug information, biomedical informatics, and clinical decision support. Workgroup members met via webinar from January 2013 to February 2014. Two in-person meetings were conducted in May and September 2013 to reach consensus on recommendations. Results We developed expert-consensus answers to three key questions: 1) What is the best approach to evaluate DDI evidence?; 2) What evidence is required for a DDI to be applicable to an entire class of drugs?; and 3) How should a structured evaluation process be vetted and validated? Conclusion Evidence-based decision support for DDIs requires consistent application of transparent and systematic methods to evaluate the evidence. Drug information systems that implement these recommendations should be able to provide higher quality information about DDIs in drug compendia and clinical decision support tools. PMID:25556085

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

NASA Astrophysics Data System (ADS)

Costanzi, Stefano; Tikhonova, Irina G.; Harden, T. Kendall; Jacobson, Kenneth A.

2009-11-01

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Chemical-Space-Based de Novo Design Method To Generate Drug-Like Molecules.

PubMed

Takeda, Shunichi; Kaneko, Hiromasa; Funatsu, Kimito

2016-10-24

To discover drug compounds in chemical space containing an enormous number of compounds, a structure generator is required to produce virtual drug-like chemical structures. The de novo design algorithm for exploring chemical space (DAECS) visualizes the activity distribution on a two-dimensional plane corresponding to chemical space and generates structures in a target area on a plane selected by the user. In this study, we modify the DAECS to enable the user to select a target area to consider properties other than activity and improve the diversity of the generated structures by visualizing the drug-likeness distribution and the activity distribution, generating structures by substructure-based structural changes, including addition, deletion, and substitution of substructures, as well as the slight structural changes used in the DAECS. Through case studies using ligand data for the human adrenergic alpha2A receptor and the human histamine H1 receptor, the modified DAECS can generate high diversity drug-like structures, and the usefulness of the modification of the DAECS is verified.

Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.

PubMed

Kaur, Divneet; Mathew, Shalu; Nair, Chinchu G S; Begum, Azitha; Jainanarayan, Ashwin K; Sharma, Mukta; Brahmachari, Samir K

2017-12-21

The problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN's Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to 'omics' data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis. In the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures. The present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery. We propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug candidates to other pathogenic organisms as well.

Exosomes as therapeutic drug carriers and delivery vehicles across biological membranes: current perspectives and future challenges.

PubMed

Ha, Dinh; Yang, Ningning; Nadithe, Venkatareddy

2016-07-01

Exosomes are small intracellular membrane-based vesicles with different compositions that are involved in several biological and pathological processes. The exploitation of exosomes as drug delivery vehicles offers important advantages compared to other nanoparticulate drug delivery systems such as liposomes and polymeric nanoparticles; exosomes are non-immunogenic in nature due to similar composition as body׳s own cells. In this article, the origin and structure of exosomes as well as their biological functions are outlined. We will then focus on specific applications of exosomes as drug delivery systems in pharmaceutical drug development. An overview of the advantages and challenges faced when using exosomes as a pharmaceutical drug delivery vehicles will also be discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manglik, Aashish; Kruse, Andrew C.; Kobilka, Tong Sun

Opium is one of the world's oldest drugs, and its derivatives morphine and codeine are among the most used clinical drugs to relieve severe pain. These prototypical opioids produce analgesia as well as many undesirable side effects (sedation, apnoea and dependence) by binding to and activating the G-protein-coupled {mu}-opioid receptor ({mu}-OR) in the central nervous system. Here we describe the 2.8 {angstrom} crystal structure of the mouse {mu}-OR in complex with an irreversible morphinan antagonist. Compared to the buried binding pocket observed in most G-protein-coupled receptors published so far, the morphinan ligand binds deeply within a large solvent-exposed pocket. Ofmore » particular interest, the {mu}-OR crystallizes as a two-fold symmetrical dimer through a four-helix bundle motif formed by transmembrane segments 5 and 6. These high-resolution insights into opioid receptor structure will enable the application of structure-based approaches to develop better drugs for the management of pain and addiction.« less

Predicting Rat and Human Pregnane X Receptor Activators Using Bayesian Classification Models.

PubMed

AbdulHameed, Mohamed Diwan M; Ippolito, Danielle L; Wallqvist, Anders

2016-10-17

The pregnane X receptor (PXR) is a ligand-activated transcription factor that acts as a master regulator of metabolizing enzymes and transporters. To avoid adverse drug-drug interactions and diseases such as steatosis and cancers associated with PXR activation, identifying drugs and chemicals that activate PXR is of crucial importance. In this work, we developed ligand-based predictive computational models for both rat and human PXR activation, which allowed us to identify potentially harmful chemicals and evaluate species-specific effects of a given compound. We utilized a large publicly available data set of nearly 2000 compounds screened in cell-based reporter gene assays to develop Bayesian quantitative structure-activity relationship models using physicochemical properties and structural descriptors. Our analysis showed that PXR activators tend to be hydrophobic and significantly different from nonactivators in terms of their physicochemical properties such as molecular weight, logP, number of rings, and solubility. Our Bayesian models, evaluated by using 5-fold cross-validation, displayed a sensitivity of 75% (76%), specificity of 76% (75%), and accuracy of 89% (89%) for human (rat) PXR activation. We identified structural features shared by rat and human PXR activators as well as those unique to each species. We compared rat in vitro PXR activation data to in vivo data by using DrugMatrix, a large toxicogenomics database with gene expression data obtained from rats after exposure to diverse chemicals. Although in vivo gene expression data pointed to cross-talk between nuclear receptor activators that is captured only by in vivo assays, overall we found broad agreement between in vitro and in vivo PXR activation. Thus, the models developed here serve primarily as efficient initial high-throughput in silico screens of in vitro activity.

Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key.

PubMed

Haupt, V Joachim; Daminelli, Simone; Schroeder, Michael

2013-01-01

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) - a drug's ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.

pH-Responsive Mesoporous Silica and Carbon Nanoparticles for Drug Delivery

PubMed Central

Gisbert-Garzarán, Miguel; Manzano, Miguel; Vallet-Regí, María

2017-01-01

The application of nanotechnology to medicine constitutes a major field of research nowadays. In particular, the use of mesoporous silica and carbon nanoparticles has attracted the attention of numerous researchers due to their unique properties, especially when applied to cancer treatment. Many strategies based on stimuli-responsive nanocarriers have been developed to control the drug release and avoid premature release. Here, we focus on the use of the subtle changes of pH between healthy and diseased areas along the body to trigger the release of the cargo. In this review, different approximations of pH-responsive systems are considered: those based on the use of the host-guest interactions between the nanocarriers and the drugs, those based on the hydrolysis of acid-labile bonds and those based on supramolecular structures acting as pore capping agents. PMID:28952481

New strategy for protein interactions and application to structure-based drug design

NASA Astrophysics Data System (ADS)

Zou, Xiaoqin

One of the greatest challenges in computational biophysics is to predict interactions between biological molecules, which play critical roles in biological processes and rational design of therapeutic drugs. Biomolecular interactions involve delicate interplay between multiple interactions, including electrostatic interactions, van der Waals interactions, solvent effect, and conformational entropic effect. Accurate determination of these complex and subtle interactions is challenging. Moreover, a biological molecule such as a protein usually consists of thousands of atoms, and thus occupies a huge conformational space. The large degrees of freedom pose further challenges for accurate prediction of biomolecular interactions. Here, I will present our development of physics-based theory and computational modeling on protein interactions with other molecules. The major strategy is to extract microscopic energetics from the information embedded in the experimentally-determined structures of protein complexes. I will also present applications of the methods to structure-based therapeutic design. Supported by NSF CAREER Award DBI-0953839, NIH R01GM109980, and the American Heart Association (Midwest Affiliate) [13GRNT16990076].

Discovery of the Highly Potent PI3K/mTOR Dual Inhibitor PF-04979064 through Structure-Based Drug Design

PubMed Central

2012-01-01

PI3K, AKT, and mTOR are key kinases from PI3K signaling pathway being extensively pursued to treat a variety of cancers in oncology. To search for a structurally differentiated back-up candidate to PF-04691502, which is currently in phase I/II clinical trials for treating solid tumors, a lead optimization effort was carried out with a tricyclic imidazo[1,5]naphthyridine series. Integration of structure-based drug design and physical properties-based optimization yielded a potent and selective PI3K/mTOR dual kinase inhibitor PF-04979064. This manuscript discusses the lead optimization for the tricyclic series, which both improved the in vitro potency and addressed a number of ADMET issues including high metabolic clearance mediated by both P450 and aldehyde oxidase (AO), poor permeability, and poor solubility. An empirical scaling tool was developed to predict human clearance from in vitro human liver S9 assay data for tricyclic derivatives that were AO substrates. PMID:24900568

Structure-based design of pteridine reductase inhibitors targeting African sleeping sickness and the leishmaniases.

PubMed

Tulloch, Lindsay B; Martini, Viviane P; Iulek, Jorge; Huggan, Judith K; Lee, Jeong Hwan; Gibson, Colin L; Smith, Terry K; Suckling, Colin J; Hunter, William N

2010-01-14

Pteridine reductase (PTR1) is a target for drug development against Trypanosoma and Leishmania species, parasites that cause serious tropical diseases and for which therapies are inadequate. We adopted a structure-based approach to the design of novel PTR1 inhibitors based on three molecular scaffolds. A series of compounds, most newly synthesized, were identified as inhibitors with PTR1-species specific properties explained by structural differences between the T. brucei and L. major enzymes. The most potent inhibitors target T. brucei PTR1, and two compounds displayed antiparasite activity against the bloodstream form of the parasite. PTR1 contributes to antifolate drug resistance by providing a molecular bypass of dihydrofolate reductase (DHFR) inhibition. Therefore, combining PTR1 and DHFR inhibitors might improve therapeutic efficacy. We tested two new compounds with known DHFR inhibitors. A synergistic effect was observed for one particular combination highlighting the potential of such an approach for treatment of African sleeping sickness.

Ultrafast protein structure-based virtual screening with Panther

NASA Astrophysics Data System (ADS)

Niinivehmas, Sanna P.; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T.

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Ultrafast protein structure-based virtual screening with Panther.

PubMed

Niinivehmas, Sanna P; Salokas, Kari; Lätti, Sakari; Raunio, Hannu; Pentikäinen, Olli T

2015-10-01

Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages (http://www.jyu.fi/panther) free of charge after registration.

Drug Release Kinetics and Transport Mechanisms of Non-degradable and Degradable Polymeric Delivery Systems

PubMed Central

Fu, Yao; Kao, Weiyuan John

2010-01-01

Importance of the field The advancement in material design and engineering has led to the rapid development of novel materials with increasing complexity and functions. Both non-degradable and degradable polymers have found wide applications in the controlled delivery field. Studies on drug release kinetics provide important information into the function of material systems. To elucidate the detailed transport mechanism and the structure-function relationship of a material system, it is critical to bridge the gap between the macroscopic data and the transport behavior at the molecular level. Areas covered in this review The structure and function information of selected non-degradable and degradable polymers have been collected and summarized from literatures published after 1990s. The release kinetics of selected drug compounds from various material systems will be discussed in case studies. Recent progresses in the mathematical models based on different transport mechanisms will be highlighted. What the reader will gain This article aims to provide an overview of structure-function relationships of selected non-degradable and degradable polymers as drug delivery matrices. Take home message Understanding the structure-function relationship of the material system is key to the successful design of a delivery system for a particular application. Moreover, developing complex polymeric matrices requires more robust mathematical models to elucidate the solute transport mechanisms. PMID:20331353

Cyclin-Dependent Kinase Inhibitors as Anticancer Therapeutics.

PubMed

Law, Mary E; Corsino, Patrick E; Narayan, Satya; Law, Brian K

2015-11-01

Cyclin-dependent kinases (CDKs) have been considered promising drug targets for a number of years, but most CDK inhibitors have failed rigorous clinical testing. Recent studies demonstrating clear anticancer efficacy and reduced toxicity of CDK4/6 inhibitors such as palbociclib and multi-CDK inhibitors such as dinaciclib have rejuvenated the field. Favorable results with palbociclib and its recent U.S. Food and Drug Administration approval demonstrate that CDK inhibitors with narrow selectivity profiles can have clinical utility for therapy based on individual tumor genetics. A brief overview of results obtained with ATP-competitive inhibitors such as palbociclib and dinaciclib is presented, followed by a compilation of new avenues that have been pursued toward the development of novel, non-ATP-competitive CDK inhibitors. These creative ways to develop CDK inhibitors are presented along with crystal structures of these agents complexed with CDK2 to highlight differences in their binding sites and mechanisms of action. The recent successes of CDK inhibitors in the clinic, combined with the potential for structure-based routes to the development of non-ATP-competitive CDK inhibitors, and evidence that CDK inhibitors may have use in suppressing chromosomal instability and in synthetic lethal drug combinations inspire optimism that CDK inhibitors will become important weapons in the fight against cancer. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Cyclin-Dependent Kinase Inhibitors as Anticancer Therapeutics

PubMed Central

Corsino, Patrick E.; Narayan, Satya

2015-01-01

Cyclin-dependent kinases (CDKs) have been considered promising drug targets for a number of years, but most CDK inhibitors have failed rigorous clinical testing. Recent studies demonstrating clear anticancer efficacy and reduced toxicity of CDK4/6 inhibitors such as palbociclib and multi-CDK inhibitors such as dinaciclib have rejuvenated the field. Favorable results with palbociclib and its recent U.S. Food and Drug Administration approval demonstrate that CDK inhibitors with narrow selectivity profiles can have clinical utility for therapy based on individual tumor genetics. A brief overview of results obtained with ATP-competitive inhibitors such as palbociclib and dinaciclib is presented, followed by a compilation of new avenues that have been pursued toward the development of novel, non–ATP-competitive CDK inhibitors. These creative ways to develop CDK inhibitors are presented along with crystal structures of these agents complexed with CDK2 to highlight differences in their binding sites and mechanisms of action. The recent successes of CDK inhibitors in the clinic, combined with the potential for structure-based routes to the development of non–ATP-competitive CDK inhibitors, and evidence that CDK inhibitors may have use in suppressing chromosomal instability and in synthetic lethal drug combinations inspire optimism that CDK inhibitors will become important weapons in the fight against cancer. PMID:26018905

Molecular Docking for Prediction and Interpretation of Adverse Drug Reactions.

PubMed

Luo, Heng; Fokoue-Nkoutche, Achille; Singh, Nalini; Yang, Lun; Hu, Jianying; Zhang, Ping

2018-05-23

Adverse drug reactions (ADRs) present a major burden for patients and the healthcare industry. Various computational methods have been developed to predict ADRs for drug molecules. However, many of these methods require experimental or surveillance data and cannot be used when only structural information is available. We collected 1,231 small molecule drugs and 600 human proteins and utilized molecular docking to generate binding features among them. We developed machine learning models that use these docking features to make predictions for 1,533 ADRs. These models obtain an overall area under the receiver operating characteristic curve (AUROC) of 0.843 and an overall area under the precision-recall curve (AUPR) of 0.395, outperforming seven structural fingerprint-based prediction models. Using the method, we predicted skin striae for fluticasone propionate, dermatitis acneiform for mometasone, and decreased libido for irinotecan, as demonstrations. Furthermore, we analyzed the top binding proteins associated with some of the ADRs, which can help to understand and/or generate hypotheses for underlying mechanisms of ADRs. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Human topoisomerase I poisoning: docking protoberberines into a structure-based binding site model

NASA Astrophysics Data System (ADS)

Kettmann, Viktor; Košt'álová, Daniela; Höltje, Hans-Dieter

2004-12-01

Using the X-ray crystal structure of the human topoisomerase I (top1) - DNA cleavable complex and the Sybyl software package, we have developed a general model for the ternary cleavable complex formed with four protoberberine alkaloids differing in the substitution on the terminal phenyl rings and covering a broad range of the top1-poisoning activities. This model has the drug intercalated with its planar chromophore between the -1 and +1 base pairs flanking the cleavage site, with the nonplanar portion pointing into the minor groove. The ternary complexes were geometry-optimized and relative interaction energies, computed by using the Tripos force field, were found to rank in correct order the biological potency of the compounds; in addition, the model is also consistent with the top1-poisoning inactivity of berberine, a major prototype of the protoberberine alkaloids. The model might serve as a rational basis for elaboration of the most active compound as a lead structure, in order to develop more potent top1 poisons as next generation anti-cancer drugs.

ADME-Space: a new tool for medicinal chemists to explore ADME properties.

PubMed

Bocci, Giovanni; Carosati, Emanuele; Vayer, Philippe; Arrault, Alban; Lozano, Sylvain; Cruciani, Gabriele

2017-07-25

We introduce a new chemical space for drugs and drug-like molecules, exclusively based on their in silico ADME behaviour. This ADME-Space is based on self-organizing map (SOM) applied to 26,000 molecules. Twenty accurate QSPR models, describing important ADME properties, were developed and, successively, used as new molecular descriptors not related to molecular structure. Applications include permeability, active transport, metabolism and bioavailability studies, but the method can be even used to discuss drug-drug interactions (DDIs) or it can be extended to additional ADME properties. Thus, the ADME-Space opens a new framework for the multi-parametric data analysis in drug discovery where all ADME behaviours of molecules are condensed in one map: it allows medicinal chemists to simultaneously monitor several ADME properties, to rapidly select optimal ADME profiles, retrieve warning on potential ADME problems and DDIs or select proper in vitro experiments.

MMpI: A WideRange of Available Compounds of Matrix Metalloproteinase Inhibitors

PubMed Central

Muvva, Charuvaka; Patra, Sanjukta; Venkatesan, Subramanian

2016-01-01

Matrix metalloproteinases (MMPs) are a family of zinc-dependent proteinases involved in the regulation of the extracellular signaling and structural matrix environment of cells and tissues. MMPs are considered as promising targets for the treatment of many diseases. Therefore, creation of database on the inhibitors of MMP would definitely accelerate the research activities in this area due to its implication in above-mentioned diseases and associated limitations in the first and second generation inhibitors. In this communication, we report the development of a new MMpI database which provides resourceful information for all researchers working in this field. It is a web-accessible, unique resource that contains detailed information on the inhibitors of MMP including small molecules, peptides and MMP Drug Leads. The database contains entries of ~3000 inhibitors including ~72 MMP Drug Leads and ~73 peptide based inhibitors. This database provides the detailed molecular and structural details which are necessary for the drug discovery and development. The MMpI database contains physical properties, 2D and 3D structures (mol2 and pdb format files) of inhibitors of MMP. Other data fields are hyperlinked to PubChem, ChEMBL, BindingDB, DrugBank, PDB, MEROPS and PubMed. The database has extensive searching facility with MMpI ID, IUPAC name, chemical structure and with the title of research article. The MMP inhibitors provided in MMpI database are optimized using Python-based Hierarchical Environment for Integrated Xtallography (Phenix) software. MMpI Database is unique and it is the only public database that contains and provides the complete information on the inhibitors of MMP. Database URL: http://clri.res.in/subramanian/databases/mmpi/index.php. PMID:27509041

Examining the production costs of antiretroviral drugs.

PubMed

Pinheiro, Eloan; Vasan, Ashwin; Kim, Jim Yong; Lee, Evan; Guimier, Jean Marc; Perriens, Joseph

2006-08-22

To present direct manufacturing costs and price calculations of individual antiretroviral drugs, enabling those responsible for their procurement to have a better understanding of the cost structure of their production, and to indicate the prices at which these antiretroviral drugs could be offered in developing country markets. Direct manufacturing costs and factory prices for selected first and second-line antiretroviral drugs were calculated based on cost structure data from a state-owned company in Brazil. Prices for the active pharmaceutical ingredients (API) were taken from a recent survey by the World Health Organization (WHO). The calculated prices for antiretroviral drugs are compared with quoted prices offered by privately-owned, for-profit manufacturers. The API represents the largest component of direct manufacturing costs (55-99%), while other inputs, such as salaries, equipment costs, and scale of production, have a minimal impact. The calculated prices for most of the antiretroviral drugs studied fall within the lower quartile of the range of quoted prices in developing country markets. The exceptions are those drugs, primarily for second-line therapy, for which the API is either under patent, in short supply, or in limited use in developing countries (e.g. abacavir, lopinavir/ritonavir, nelfinavir, saquinavir). The availability of data on the cost of antiretroviral drug production and calculation of factory prices under a sustainable business model provide benchmarks that bulk purchasers of antiretroviral drugs could use to negotiate lower prices. While truly significant price decreases for antiretroviral drugs will depend largely on the future evolution of API prices, the present study demonstrates that for several antiretroviral drugs price reduction is currently possible. Whether or not these reductions materialize will depend on the magnitude of indirect cost and profit added by each supplier over the direct production costs. The ability to achieve price reductions in line with production costs will have critical implications for sustainable treatment for HIV/AIDS in the developing world.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

Oral and transdermal drug delivery systems: role of lipid-based lyotropic liquid crystals.

PubMed

Rajabalaya, Rajan; Musa, Muhammad Nuh; Kifli, Nurolaini; David, Sheba R

2017-01-01

Liquid crystal (LC) dosage forms, particularly those using lipid-based lyotropic LCs (LLCs), have generated considerable interest as potential drug delivery systems. LCs have the physical properties of liquids but retain some of the structural characteristics of crystalline solids. They are compatible with hydrophobic and hydrophilic compounds of many different classes and can protect even biologicals and nucleic acids from degradation. This review, focused on research conducted over the past 5 years, discusses the structural evaluation of LCs and their effects in drug formulations. The structural classification of LLCs into lamellar, hexagonal and micellar cubic phases is described. The structures of these phases are influenced by the addition of surfactants, which include a variety of nontoxic, biodegradable lipids; these also enhance drug solubility. LLC structure influences drug localization, particle size and viscosity, which, in turn, determine drug delivery properties. Through several specific examples, we describe the applications of LLCs in oral and topical drug formulations, the latter including transdermal and ocular delivery. In oral LLC formulations, micelle compositions and the resulting LLC structures can determine drug solubilization and stability as well as intestinal transport and absorption. Similarly, in topical LLC formulations, composition can influence whether the drug is retained in the skin or delivered transdermally. Owing to their enhancement of drug stability and promotion of controlled drug delivery, LLCs are becoming increasingly popular in pharmaceutical formulations.

Oral and transdermal drug delivery systems: role of lipid-based lyotropic liquid crystals

PubMed Central

Rajabalaya, Rajan; Musa, Muhammad Nuh; Kifli, Nurolaini; David, Sheba R

2017-01-01

Liquid crystal (LC) dosage forms, particularly those using lipid-based lyotropic LCs (LLCs), have generated considerable interest as potential drug delivery systems. LCs have the physical properties of liquids but retain some of the structural characteristics of crystalline solids. They are compatible with hydrophobic and hydrophilic compounds of many different classes and can protect even biologicals and nucleic acids from degradation. This review, focused on research conducted over the past 5 years, discusses the structural evaluation of LCs and their effects in drug formulations. The structural classification of LLCs into lamellar, hexagonal and micellar cubic phases is described. The structures of these phases are influenced by the addition of surfactants, which include a variety of nontoxic, biodegradable lipids; these also enhance drug solubility. LLC structure influences drug localization, particle size and viscosity, which, in turn, determine drug delivery properties. Through several specific examples, we describe the applications of LLCs in oral and topical drug formulations, the latter including transdermal and ocular delivery. In oral LLC formulations, micelle compositions and the resulting LLC structures can determine drug solubilization and stability as well as intestinal transport and absorption. Similarly, in topical LLC formulations, composition can influence whether the drug is retained in the skin or delivered transdermally. Owing to their enhancement of drug stability and promotion of controlled drug delivery, LLCs are becoming increasingly popular in pharmaceutical formulations. PMID:28243062

Crystal structure of the μ-opioid receptor bound to a morphinan antagonist

PubMed Central

Manglik, Aashish; Kruse, Andrew C.; Kobilka, Tong Sun; Thian, Foon Sun; Mathiesen, Jesper M.; Sunahara, Roger K.; Pardo, Leonardo; Weis, William I.; Kobilka, Brian K.; Granier, Sébastien

2012-01-01

Summary Opium is one of the world’s oldest drugs, and its derivatives morphine and codeine are among the most used clinical drugs to relieve severe pain. These prototypical opioids produce analgesia as well as many of their undesirable side effects (sedation, apnea and dependence) by binding to and activating the G-protein-coupled μ-opioid receptor (μOR) in the central nervous system. Here we describe the 2.8 Å crystal structure of the μOR in complex with an irreversible morphinan antagonist. Compared to the buried binding pocket observed in most GPCRs published to date, the morphinan ligand binds deeply within a large solvent-exposed pocket. Of particular interest, the μOR crystallizes as a two-fold symmetric dimer through a four-helix bundle motif formed by transmembrane segments 5 and 6. These high-resolution insights into opioid receptor structure will enable the application of structure-based approaches to develop better drugs for the management of pain and addiction. PMID:22437502

What Can Crystal Structures of Aminergic Receptors Tell Us about Designing Subtype-Selective Ligands?

PubMed Central

Michino, Mayako; Beuming, Thijs; Donthamsetti, Prashant; Newman, Amy Hauck; Javitch, Jonathan A.

2015-01-01

G protein–coupled receptors (GPCRs) are integral membrane proteins that represent an important class of drug targets. In particular, aminergic GPCRs interact with a significant portion of drugs currently on the market. However, most drugs that target these receptors are associated with undesirable side effects, which are due in part to promiscuous interactions with close homologs of the intended target receptors. Here, based on a systematic analysis of all 37 of the currently available high-resolution crystal structures of aminergic GPCRs, we review structural elements that contribute to and can be exploited for designing subtype-selective compounds. We describe the roles of secondary binding pockets (SBPs), as well as differences in ligand entry pathways to the orthosteric binding site, in determining selectivity. In addition, using the available crystal structures, we have identified conformational changes in the SBPs that are associated with receptor activation and explore the implications of these changes for the rational development of selective ligands with tailored efficacy. PMID:25527701

Bacterial Transcription as a Target for Antibacterial Drug Development

PubMed Central

Ma, Cong; Yang, Xiao

2016-01-01

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

Droplet-born air blowing: novel dissolving microneedle fabrication.

PubMed

Kim, Jung Dong; Kim, Miroo; Yang, Huisuk; Lee, Kwang; Jung, Hyungil

2013-09-28

The microneedle-mediated drug delivery system has been developed to provide painless self-administration of drugs in a patient-friendly manner. Current dissolving microneedle fabrication methods, however, require harsh conditions for biological drugs and also have problems standardizing the drug dose. Here, we suggested the droplet-born air blowing (DAB) method, which provides gentle (4-25 °C) and fast (≤10min) microneedle fabrication conditions without drug loss. The amount of drug in the microneedle can be controlled by the pressure and time of droplet dispenser and the air blowing shapes this droplet to the microneedle, providing a force sufficient to penetrate skin. Also, the introduction of a base structure of two layered DAB-microneedle could provide complete drug delivery without wasting of drug. The DAB-based insulin loaded microneedle shows similar bioavailability (96.6±2.4%) and down regulation of glucose level compared with subcutaneous injection. We anticipate that DAB described herein will be suitable to design dissolving microneedles for use in biological drug delivery to patients. Copyright © 2013 Elsevier B.V. All rights reserved.

Capturing Biological Activity in Natural Product Fragments by Chemical Synthesis

PubMed Central

Crane, Erika A.

2016-01-01

Abstract Natural products have had an immense influence on science and have directly led to the introduction of many drugs. Organic chemistry, and its unique ability to tailor natural products through synthesis, provides an extraordinary approach to unlock the full potential of natural products. In this Review, an approach based on natural product derived fragments is presented that can successfully address some of the current challenges in drug discovery. These fragments often display significantly reduced molecular weights, reduced structural complexity, a reduced number of synthetic steps, while retaining or even improving key biological parameters such as potency or selectivity. Examples from various stages of the drug development process up to the clinic are presented. In addition, this process can be leveraged by recent developments such as genome mining, antibody–drug conjugates, and computational approaches. All these concepts have the potential to identify the next generation of drug candidates inspired by natural products. PMID:26833854

Brazil: An emerging partner in drug R&D.

PubMed

Rodrigues, Debora G

2009-08-01

With the need for innovation in drug discovery and development and changes to patent laws that are enabling greater IP protection, many pharmaceutical companies are pursuing international cooperation agreements with foreign companies as part of a global development strategy to enhance product pipelines. Brazil, the largest pharmaceutical market in Latin America, has improved its infrastructure, scientific and technological capabilities and has created a sustainable strategy to promote drug discovery research activities. Positive economic growth, a stable political structure, expanding patient populations an increasing governmental, private and foreign investments are creating a new landscape for drug R&D in the country. As Brazilian-based pharmaceutical companies become further established, new opportunities for partnerships and collaborative alliances are becoming available for the drug discovery process, as well as for co-manufacturing and co-marketing efforts. This feature review provides an overview of the Brazilian pharmaceutical market and discusses current opportunities, emerging trends and challenges for this expanding market.

Common Drugs for Stabilization of Renal Function in the Progression of Diabetic Nephropathy and Their Relations with Hypertension Therapy.

PubMed

Wang, Yuxuan; Wang, Chengcheng; Zhang, Xiuli; Gu, Harvest F; Wu, Liang

2018-01-01

Diabetic nephropathy is characterized by hypertension, progressive albuminuria, glomerulosclerosis and declines in glomerular filtration rate leading to end stage renal disease. Although the pathogenesis of diabetic nephropathy is not fully understood, current treatment of the patients with diabetic nephropathy is mainly based upon the control of hyperglycaemia and management of blood pressures. Several drugs, which are originally developed for hypertension therapy, have been adopted for stabilization of renal function in diabetic nephropathy. In this review, we first discussed the relationships between diabetic nephropathy and hypertension particularly in the renin-angiotensinaldosterone system. We then summarized chemical structures, pharmacological characteristics and clinical studies of the common drugs used for treatment of diabetic nephropathy, while these drugs have effects against hypertension. This review may provide the constructive information for further drug development in diabetic nephropathy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

EPOR-Based Purification and Analysis of Erythropoietin Mimetic Peptides from Human Urine by Cys-Specific Cleavage and LC/MS/MS

NASA Astrophysics Data System (ADS)

Vogel, Matthias; Thomas, Andreas; Schänzer, Wilhelm; Thevis, Mario

2015-09-01

The development of a new class of erythropoietin mimetic agents (EMA) for treating anemic conditions has been initiated with the discovery of oligopeptides capable of dimerizing the erythropoietin (EPO) receptor and thus stimulating erythropoiesis. The most promising amino acid sequences have been mounted on various different polymeric structures or carrier molecules to obtain highly active EPO-like drugs exhibiting beneficial and desirable pharmacokinetic profiles. Concomitant with creating new therapeutic options, erythropoietin mimetic peptide (EMP)-based drug candidates represent means to artificially enhance endurance performance and necessitate coverage by sports drug testing methods. Therefore, the aim of the present study was to develop a strategy for the comprehensive detection of EMPs in doping controls, which can be used complementary to existing protocols. Three model EMPs were used to provide proof-of-concept data. Following EPO receptor-facilitated purification of target analytes from human urine, the common presence of the cysteine-flanked core structure of EMPs was exploited to generate diagnostic peptides with the aid of a nonenzymatic cleavage procedure. Sensitive detection was accomplished by targeted-SIM/data-dependent MS2 analysis. Method characterization was conducted for the EMP-based drug peginesatide concerning specificity, linearity, precision, recovery, stability, ion suppression/enhancement, and limit of detection (LOD, 0.25 ng/mL). Additionally, first data for the identification of the erythropoietin mimetic peptides EMP1 and BB68 were generated, demonstrating the multi-analyte testing capability of the presented approach.

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

Characterization and Higher-Order Structure Assessment of an Interchain Cysteine-Based ADC: Impact of Drug Loading and Distribution on the Mechanism of Aggregation.

PubMed

Guo, Jianxin; Kumar, Sandeep; Chipley, Mark; Marcq, Olivier; Gupta, Devansh; Jin, Zhaowei; Tomar, Dheeraj S; Swabowski, Cecily; Smith, Jacquelynn; Starkey, Jason A; Singh, Satish K

2016-03-16

The impact of drug loading and distribution on higher order structure and physical stability of an interchain cysteine-based antibody drug conjugate (ADC) has been studied. An IgG1 mAb was conjugated with a cytotoxic auristatin payload following the reduction of interchain disulfides. The 2-D LC-MS analysis shows that there is a preference for certain isomers within the various drug to antibody ratios (DARs). The physical stability of the unconjugated monoclonal antibody, the ADC, and isolated conjugated species with specific DAR, were compared using calorimetric, thermal, chemical denaturation and molecular modeling techniques, as well as techniques to assess hydrophobicity. The DAR was determined to have a significant impact on the biophysical properties and stability of the ADC. The CH2 domain was significantly perturbed in the DAR6 species, which was attributable to quaternary structural changes as assessed by molecular modeling. At accelerated storage temperatures, the DAR6 rapidly forms higher molecular mass species, whereas the DAR2 and the unconjugated mAb were largely stable. Chemical denaturation study indicates that DAR6 may form multimers while DAR2 and DAR4 primarily exist in monomeric forms in solution at ambient conditions. The physical state differences were correlated with a dramatic increase in the hydrophobicity and a reduction in the surface tension of the DAR6 compared to lower DAR species. Molecular modeling of the various DAR species and their conformers demonstrates that the auristatin-based linker payload directly contributes to the hydrophobicity of the ADC molecule. Higher order structural characterization provides insight into the impact of conjugation on the conformational and colloidal factors that determine the physical stability of cysteine-based ADCs, with implications for process and formulation development.

Development and characterization of a novel drug nanocarrier for oral delivery, based on self-assembled β-casein micelles.

PubMed

Bachar, Michal; Mandelbaum, Amitai; Portnaya, Irina; Perlstein, Hadas; Even-Chen, Simcha; Barenholz, Yechezkel; Danino, Dganit

2012-06-10

β-casein is an amphiphilic protein that self-organizes into well-defined core-shell micelles. We developed these micelles as efficient nanocarriers for oral drug delivery. Our model drug is celecoxib, an anti-inflammatory hydrophobic drug utilized for treatment of rheumatoid arthritis and osteoarthritis, now also evaluated as a potent anticancer drug. This system is unique as it enables encapsulation loads >100-fold higher than other β-casein/drug formulations, and does not require additives as do other formulations that have high loadings. This is combined with the ability to lyophilize the formulation without a cryoprotectant, long-term physical and chemical stability of the resulting powder, and fully reversible reconstitution of the structures by rehydration. The dry dosage form, in which >95% of the drug is encapsulated, meets the daily dose. Cryo-TEM and DLS prove that drug encapsulation results in micelle swelling, and X-ray diffraction shows that the encapsulated drug is amorphous. Altogether, our novel dosage form is highly advantageous for oral administration. Copyright © 2012 Elsevier B.V. All rights reserved.

Solution NMR Spectroscopy in Target-Based Drug Discovery.

PubMed

Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

PubMed Central

Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

PubMed

Fang, Ye; Ding, Yun; Feinstein, Wei P; Koppelman, David M; Moreno, Juana; Jarrell, Mark; Ramanujam, J; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Graph-based similarity concepts in virtual screening.

PubMed

Hutter, Michael C

2011-03-01

Applying similarity for finding new promising compounds is a key issue in drug design. Conversely, quantifying similarity between molecules has remained a difficult task despite the numerous approaches. Here, some general aspects along with recent developments regarding similarity criteria are collected. For the purpose of virtual screening, the compounds have to be encoded into a computer-readable format that permits a comparison, according to given similarity criteria, comprising the use of the 3D structure, fingerprints, graph-based and alignment-based approaches. Whereas finding the most common substructures is the most obvious method, more recent approaches take into account chemical modifications that appear throughout existing drugs, from various therapeutic categories and targets.

Structural interaction fingerprints: a new approach to organizing, mining, analyzing, and designing protein-small molecule complexes.

PubMed

Singh, Juswinder; Deng, Zhan; Narale, Gaurav; Chuaqui, Claudio

2006-01-01

The combination of advances in structure-based drug design efforts in the pharmaceutical industry in parallel with structural genomics initiatives in the public domain has led to an explosion in the number of structures of protein-small molecule complexes structures. This information has critical importance to both the understanding of the structural basis for molecular recognition in biological systems and the design of better drugs. A significant challenge exists in managing this vast amount of data and fully leveraging it. Here, we review our work to develop a simple, fast way to store, organize, mine, and analyze large numbers of protein-small molecule complexes. We illustrate the utility of the approach to the management of inhibitor complexes from the protein kinase family. Finally, we describe our recent efforts in applying this method to the design of target-focused chemical libraries.

Identification of Direct Activator of Adenosine Monophosphate-Activated Protein Kinase (AMPK) by Structure-Based Virtual Screening and Molecular Docking Approach.

PubMed

Huang, Tonghui; Sun, Jie; Zhou, Shanshan; Gao, Jian; Liu, Yi

2017-06-30

Adenosine monophosphate-activated protein kinase (AMPK) plays a critical role in the regulation of energy metabolism and has been targeted for drug development of therapeutic intervention in Type II diabetes and related diseases. Recently, there has been renewed interest in the development of direct β1-selective AMPK activators to treat patients with diabetic nephropathy. To investigate the details of AMPK domain structure, sequence alignment and structural comparison were used to identify the key amino acids involved in the interaction with activators and the structure difference between β1 and β2 subunits. Additionally, a series of potential β1-selective AMPK activators were identified by virtual screening using molecular docking. The retrieved hits were filtered on the basis of Lipinski's rule of five and drug-likeness. Finally, 12 novel compounds with diverse scaffolds were obtained as potential starting points for the design of direct β1-selective AMPK activators.

Thiazolidine-2,4-dione derivatives: programmed chemical weapons for key protein targets of various pathological conditions.

PubMed

Chadha, Navriti; Bahia, Malkeet Singh; Kaur, Maninder; Silakari, Om

2015-07-01

Thiazolidine-2,4-dione is an extensively explored heterocyclic nucleus for designing of novel agents implicated for a wide variety of pathophysiological conditions, that is, diabetes, diabetic complications, cancer, arthritis, inflammation, microbial infection, and melanoma, etc. The current paradigm of drug development has shifted to the structure-based drug design, since high-throughput screenings have continued to generate disappointing results. The gap between hit generation and drug establishment can be narrowed down by investigation of ligand interactions with its receptor protein. Therefore, it would always be highly beneficial to gain knowledge of molecular level interactions between specific protein target and developed ligands; since this information can be maneuvered to design new molecules with improved protein fitting. Thus, considering this aspect, we have corroborated the information about molecular (target) level implementations of thiazolidine-2,4-diones (TZD) derivatives having therapeutic implementations such as, but not limited to, anti-diabetic (glitazones), anti-cancer, anti-arthritic, anti-inflammatory, anti-oxidant and anti-microbial, etc. The structure based SAR of TZD derivatives for various protein targets would serve as a benchmark for the alteration of existing ligands to design new ones with better binding interactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nitric oxide-sensing actuators for modulating structure in lipid-based liquid crystalline drug delivery systems.

PubMed

Liu, Qingtao; Hu, Jinming; Whittaker, Michael R; Davis, Thomas P; Boyd, Ben J

2017-12-15

Herein we report on the development of a nitric oxide-sensing lipid-based liquid crystalline (LLC) system specifically designed to release encapsulated drugs on exposure to NO through a stimulated phase change. A series of nitric oxide (NO)-sensing lipids compatible with phytantriol and GMO cubic phases were designed and synthesized, and utilized in enabling nitric oxide-sensing LLC systems. The nitric oxide (NO)-sensing lipids react with nitric oxide, resulting in hydrolysis of these lipids and phase transition of the LLC system. Specifically, the N-3-aminopyridinyl myristylamine (NAPyM)+phytantriol mixture formed a lamellar phase in excess aqueous environment. The NAPyM+phytantriol LLC responded to the nitric oxide gas as a chemical stimulus which triggers a phase transition from lamellar phase to inverse cubic and hexagonal phase. The nitric oxide-triggered phase transition of the LLC accelerated the release of encapsulated model drug from the LLC bulk phase, resulting in a 15-fold increase in the diffusion coefficient compared to the starting lamellar structure. The nitric oxide-sensing LLC system has potential application in the development of smart medicines to treat nitric oxide implicated diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Integrating structure-based and ligand-based approaches for computational drug design.

PubMed

Wilson, Gregory L; Lill, Markus A

2011-04-01

Methods utilized in computer-aided drug design can be classified into two major categories: structure based and ligand based, using information on the structure of the protein or on the biological and physicochemical properties of bound ligands, respectively. In recent years there has been a trend towards integrating these two methods in order to enhance the reliability and efficiency of computer-aided drug-design approaches by combining information from both the ligand and the protein. This trend resulted in a variety of methods that include: pseudoreceptor methods, pharmacophore methods, fingerprint methods and approaches integrating docking with similarity-based methods. In this article, we will describe the concepts behind each method and selected applications.

Rho kinase inhibitors: a patent review (2012 - 2013).

PubMed

Feng, Yangbo; LoGrasso, Philip V

2014-03-01

The Rho kinase/ROCK is critical in vital signal transduction pathways central to many essential cellular activities. Since ROCK possess multiple substrates, modulation of ROCK activity is useful for treatment of many diseases. Significant progress has been made in the development of ROCK inhibitors over the past two years (Jan 2012 to Aug 2013). Patent search in this review was based on FPO IP Research and Communities and Espacenet Patent Search. In this review, patent applications will be classified into four groups for discussions. The grouping is mainly based on structures or scaffolds (groups 1 and 2) and biological functions of ROCK inhibitors (groups 3 and 4). These four groups are i) ROCK inhibitors based on classical structural elements for ROCK inhibition; ii) ROCK inhibitors based on new scaffolds; iii) bis-functional ROCK inhibitors; and iv) novel applications of ROCK inhibitors. Although currently only one ROCK inhibitor (fasudil) is used as a drug, more drugs based on ROCK inhibition are expected to be advanced into market in the near future. Several directions should be considered for future development of ROCK inhibitors, such as soft ROCK inhibitors, bis-functional ROCK inhibitors, ROCK2 isoform-selective inhibitors, and ROCK inhibitors as antiproliferation agents.

Structure–activity relationships study of mTOR kinase inhibition using QSAR and structure-based drug design approaches

PubMed Central

Lakhlili, Wiame; Yasri, Abdelaziz; Ibrahimi, Azeddine

2016-01-01

The discovery of clinically relevant inhibitors of mammalian target of rapamycin (mTOR) for anticancer therapy has proved to be a challenging task. The quantitative structure–activity relationship (QSAR) approach is a very useful and widespread technique for ligand-based drug design, which can be used to identify novel and potent mTOR inhibitors. In this study, we performed two-dimensional QSAR tests, and molecular docking validation tests of a series of mTOR ATP-competitive inhibitors to elucidate their structural properties associated with their activity. The QSAR tests were performed using partial least square method with a correlation coefficient of r2=0.799 and a cross-validation of q2=0.714. The chemical library screening was done by associating ligand-based to structure-based approach using the three-dimensional structure of mTOR developed by homology modeling. We were able to select 22 compounds from two databases as inhibitors of the mTOR kinase active site. We believe that the method and applications highlighted in this study will help future efforts toward the design of selective ATP-competitive inhibitors. PMID:27980424

Prevention of IcaA regulated poly N-acetyl glucosamine formation in Staphylococcus aureus biofilm through new-drug like inhibitors: In silico approach and MD simulation study.

PubMed

Gupta, Ayushi; Mishra, Swechha; Singh, Sangeeta; Mishra, Sonali

2017-09-01

The effectiveness of various ligands against the protein structure of IcaA of the IcaABCD gene locus of Staphylococcus aureus were examined using the approach of structure based drug designing in reference with the protein's efficiency to form biofilms. Four compounds CID42738592, CID90468752, CID24277882, and CID6435208 were secluded from a database of 31,242 inhibitory ligands on the justification of the evaluated values falling under the four - tier structure based virtual screening. Under this principle value of least binding energy, human oral absorption and ADME properties were taken into consideration. Using the Glide module of Schrödinger, the above mentioned ligands showed an effective action against the protein IcaA which showed reduced activity as a glucosaminyl transferase. The complex of protein and ligand with best docking score was chosen for simulation studies. Structure based drug designing for the protein IcaA has given us potential leads as anti - biofilm agents. These screened out ligands might enable the development of new therapeutic strategies aimed at disrupting Staphylococcus aureus biofilms. The complex was showing stability towards the end of time for which it has been put for simulation. Thus molecule could be considered for making of biofilms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Efficient method for high-throughput virtual screening based on flexible docking: discovery of novel acetylcholinesterase inhibitors.

PubMed

Mizutani, Miho Yamada; Itai, Akiko

2004-09-23

A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.

Drug target ontology to classify and integrate drug discovery data.

PubMed

Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

2017-11-09

One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs.

PubMed

Liu, Mei; Wu, Yonghui; Chen, Yukun; Sun, Jingchun; Zhao, Zhongming; Chen, Xue-wen; Matheny, Michael Edwin; Xu, Hua

2012-06-01

Adverse drug reaction (ADR) is one of the major causes of failure in drug development. Severe ADRs that go undetected until the post-marketing phase of a drug often lead to patient morbidity. Accurate prediction of potential ADRs is required in the entire life cycle of a drug, including early stages of drug design, different phases of clinical trials, and post-marketing surveillance. Many studies have utilized either chemical structures or molecular pathways of the drugs to predict ADRs. Here, the authors propose a machine-learning-based approach for ADR prediction by integrating the phenotypic characteristics of a drug, including indications and other known ADRs, with the drug's chemical structures and biological properties, including protein targets and pathway information. A large-scale study was conducted to predict 1385 known ADRs of 832 approved drugs, and five machine-learning algorithms for this task were compared. This evaluation, based on a fivefold cross-validation, showed that the support vector machine algorithm outperformed the others. Of the three types of information, phenotypic data were the most informative for ADR prediction. When biological and phenotypic features were added to the baseline chemical information, the ADR prediction model achieved significant improvements in area under the curve (from 0.9054 to 0.9524), precision (from 43.37% to 66.17%), and recall (from 49.25% to 63.06%). Most importantly, the proposed model successfully predicted the ADRs associated with withdrawal of rofecoxib and cerivastatin. The results suggest that phenotypic information on drugs is valuable for ADR prediction. Moreover, they demonstrate that different models that combine chemical, biological, or phenotypic information can be built from approved drugs, and they have the potential to detect clinically important ADRs in both preclinical and post-marketing phases.

Structure-based virtual screening efforts against HIV-1 reverse transcriptase to introduce the new potent non-nucleoside reverse transcriptase inhibitor

NASA Astrophysics Data System (ADS)

Hosseini, Yaser; Mollica, Adriano; Mirzaie, Sako

2016-12-01

The human immunodeficiency virus (HIV) which is strictly related to the development of AIDS, is treated by a cocktail of drugs, but due its high propensity gain drug resistance, the rational development of new medicine is highly desired. Among the different mechanism of action we selected the reverse transcriptase (RT) inhibition, for our studies. With the aim to identify new chemical entities to be used for further rational drug design, a set of 3000 molecules from the Zinc Database have been screened by docking experiments using AutoDock Vina software. The best ranked compounds with respect of the crystallographic inhibitor MK-4965 resulted to be five compounds, and the best among them was further tested by molecular dynamics (MD) simulation. Our results indicate that comp1 has a stronger interaction with the subsite p66 of RT than MK-4965 and that both are able to stabilize specific conformational changes of the RT 3D structure, which may explain their activity as inhibitors. Therefore comp1 could be a good candidate for biological tests and further development.

Recommendations of the Oligonucleotide Safety Working Group's Formulated Oligonucleotide Subcommittee for the Safety Assessment of Formulated Oligonucleotide-Based Therapeutics.

PubMed

Marlowe, Jennifer L; Akopian, Violetta; Karmali, Priya; Kornbrust, Douglas; Lockridge, Jennifer; Semple, Sean

2017-08-01

The use of lipid formulations has greatly improved the ability to effectively deliver oligonucleotides and has been instrumental in the rapid expansion of therapeutic development programs using oligonucleotide drugs. However, the development of such complex multicomponent therapeutics requires the implementation of unique, scientifically sound approaches to the nonclinical development of these drugs, based upon a hybrid of knowledge and experiences drawn from small molecule, protein, and oligonucleotide therapeutic drug development. The relative paucity of directly applicable regulatory guidance documents for oligonucleotide therapeutics in general has resulted in the generation of multiple white papers from oligonucleotide drug development experts and members of the Oligonucleotide Safety Working Group (OSWG). The members of the Formulated Oligonucleotide Subcommittee of the OSWG have utilized their collective experience working with a variety of formulations and their associated oligonucleotide payloads, as well as their insights into regulatory considerations and expectations, to generate a series of consensus recommendations for the pharmacokinetic characterization and nonclinical safety assessment of this unique class of therapeutics. It should be noted that the focus of Subcommittee discussions was on lipid nanoparticle and other types of particulate formulations of therapeutic oligonucleotides and not on conjugates or other types of modifications of oligonucleotide structure intended to facilitate delivery.

Medicinal chemistry inspired fragment-based drug discovery.

PubMed

Lanter, James; Zhang, Xuqing; Sui, Zhihua

2011-01-01

Lead generation can be a very challenging phase of the drug discovery process. The two principal methods for this stage of research are blind screening and rational design. Among the rational or semirational design approaches, fragment-based drug discovery (FBDD) has emerged as a useful tool for the generation of lead structures. It is particularly powerful as a complement to high-throughput screening approaches when the latter failed to yield viable hits for further development. Engagement of medicinal chemists early in the process can accelerate the progression of FBDD efforts by incorporating drug-friendly properties in the earliest stages of the design process. Medium-chain acyl-CoA synthetase 2b and ketohexokinase are chosen as examples to illustrate the importance of close collaboration of medicinal chemists, crystallography, and modeling. Copyright © 2011 Elsevier Inc. All rights reserved.

Aptamer-Mediated Up-conversion Core/MOF Shell Nanocomposites for Targeted Drug Delivery and Cell Imaging

PubMed Central

Deng, Kerong; Hou, Zhiyao; Li, Xuejiao; Li, Chunxia; Zhang, Yuanxin; Deng, Xiaoran; Cheng, Ziyong; Lin, Jun

2015-01-01

Multifunctional nanocarriers for targeted bioimaging and drug delivery have attracted much attention in early diagnosis and therapy of cancer. In this work, we develop a novel aptamer-guided nanocarrier based on the mesoporous metal-organic framework (MOF) shell and up-conversion luminescent NaYF4:Yb3+/Er3+ nanoparticles (UCNPs) core for the first time to achieve these goals. These UCNPs, chosen as optical labels in biological assays and medical imaging, could emit strong green emission under 980 nm laser. The MOF structure based on iron (III) carboxylate materials [MIL-100 (Fe)] possesses high porosity and non-toxicity, which is of great value as nanocarriers for drug storage/delivery. As a unique nanoplatform, the hybrid inorganic-organic drug delivery vehicles show great promising for simultaneous targeted labeling and therapy of cancer cells. PMID:25597762

Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions.

PubMed

Lipinski, Christopher A

2016-06-01

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Thermostabilisation of membrane proteins for structural studies

PubMed Central

Magnani, Francesca; Serrano-Vega, Maria J.; Shibata, Yoko; Abdul-Hussein, Saba; Lebon, Guillaume; Miller-Gallacher, Jennifer; Singhal, Ankita; Strege, Annette; Thomas, Jennifer A.; Tate, Christopher G.

2017-01-01

The thermostability of an integral membrane protein in detergent solution is a key parameter that dictates the likelihood of obtaining well-diffracting crystals suitable for structure determination. However, many mammalian membrane proteins are too unstable for crystallisation. We developed a thermostabilisation strategy based on systematic mutagenesis coupled to a radioligand-binding thermostability assay that can be applied to receptors, ion channels and transporters. It takes approximately 6-12 months to thermostabilise a G protein-coupled receptor (GPCR) containing 300 amino acid residues. The resulting thermostabilised membrane proteins are more easily crystallised and result in high-quality structures. This methodology has facilitated structure-based drug design applied to GPCRs, because it is possible to determine multiple structures of the thermostabilised receptors bound to low affinity ligands. Protocols and advice are given on how to develop thermostability assays for membrane proteins and how to combine mutations to make an optimally stable mutant suitable for structural studies. PMID:27466713

Exploring the molecular basis of dsRNA recognition by NS1 protein of influenza A virus using molecular dynamics simulation and free energy calculation.

PubMed

Pan, Dabo; Sun, Huijun; Shen, Yulin; Liu, Huanxiang; Yao, Xiaojun

2011-12-01

The frequent outbreak of influenza pandemic and the limited available anti-influenza drugs highlight the urgent need for the development of new antiviral drugs. The dsRNA-binding surface of nonstructural protein 1 of influenza A virus (NS1A) is a promising target. The detailed understanding of NS1A-dsRNA interaction will be valuable for structure-based anti-influenza drug discovery. To characterize and explore the key interaction features between dsRNA and NS1A, molecular dynamics simulation combined with MM-GBSA calculations were performed. Based on the MM-GBSA calculations, we find that the intermolecular van der Waals interaction and the nonpolar solvation term provide the main driving force for the binding process. Meanwhile, 17 key residues from NS1A were identified to be responsible for the dsRNA binding. Compared with the wild type NS1A, all the studied mutants S42A, T49A, R38A, R35AR46A have obvious reduced binding free energies with dsRNA reflecting in the reduction of the polar and/or nonpolar interactions. In addition, the structural and energy analysis indicate the mutations have a small effect to the backbone structures but the loss of side chain interactions is responsible for the decrease of the binding affinity. The uncovering of NS1A-dsRNA recognition mechanism will provide some useful insights and new chances for the development of anti-influenza drugs. Copyright © 2011 Elsevier B.V. All rights reserved.

Research strategies for design and development of NSAIDs: clue to balance potency and toxicity of acetanilide compounds.

PubMed

Pal, A K; Sen, S; Ghosh, S; Bera, A K; Bhattacharya, S; Chakraborty, S; Banerjee, A

2001-08-01

Despite the fact that many modern drug therapies are based on the concept of enzyme inhibition, inhibition of several enzymes leads to pathological disorders. Clinically used nonsteroidal anti-inflammatory drugs (NSAIDs) bind to the active site of the membrane protein, cyclooxygenase (COX) and inhibit the synthesis of prostaglandins, the mediators for causing inflammation. At the same time, inhibition of hepatic cysteine proteases by some NSAID metabolites like NAPQI is implicated in the pathogenesis of hepatotoxicity. As a part of our efforts to develop new effective NSAIDs, a comprehensive investigation starting from synthesis to the study of the final metabolism of acetanilide group of compound has been envisaged with appropriate feedback from kinetic studies to enhance our knowledge and technical competency to feed the know-how to the medicinal chemist to screen out and design new acetanilide derivatives of high potency and low toxicity. Structure-function relationship based on the interaction of acetanilide with its cognate enzyme, cyclooxygenase has been studied critically with adequate comparison with several other available crystal structures of COX-NSAID complexes. Furthermore, to make the receptor based drug design strategy a novel and comprehensive one, both the mechanism of metabolism of acetanilide and structural basis of inhibition of cysteine proteases by the reactive metabolite (NAPQI) formed by cytochrome P450 oxidation of acetanilide have been incorporated in the study. It is hoped that this synergistic approach and the results obtained from such consorted structural investigation at atomic level may guide to dictate synthetic modification with judicious balance between cyclooxygenase inhibition and hepatic cysteine protease inhibition to enhance the potential of such molecular medicine to relieve inflammation on one hand and low hepatic toxicity on the other.

Preparation and investigation of novel gastro-floating tablets with 3D extrusion-based printing.

PubMed

Li, Qijun; Guan, Xiaoying; Cui, Mengsuo; Zhu, Zhihong; Chen, Kai; Wen, Haoyang; Jia, Danyang; Hou, Jian; Xu, Wenting; Yang, Xinggang; Pan, Weisan

2018-01-15

Three dimensional (3D) extrusion-based printing is a paste-based rapid prototyping process, which is capable of building complex 3D structures. The aim of this study was to explore the feasibility of 3D extrusion-based printing as a pharmaceutical manufacture technique for the fabrication of gastro-floating tablets. Novel low-density lattice internal structure gastro-floating tablets of dipyridamole were developed to prolong the gastric residence time in order to improve drug release rate and consequently, improve bioavailability and therapeutic efficacy. Excipients commonly employed in the pharmaceutical study could be efficiently applied in the room temperature 3D extrusion-based printing process. The tablets were designed with three kinds of infill percentage and prepared by hydroxypropyl methylcellulose (HPMC K4M) and hydroxypropyl methylcellulose (HPMC E15) as hydrophilic matrices and microcrystalline cellulose (MCC PH101) as extrusion molding agent. In vitro evaluation of the 3D printed gastro-floating tablets was performed by determining mechanical properties, content uniformity, and weight variation. Furthermore, re-floating ability, floating duration time, and drug release behavior were also evaluated. Dissolution profiles revealed the relationship between infill percentage and drug release behavior. The results of this study revealed the potential of 3D extrusion-based printing to fabricate gastro-floating tablets with more than 8h floating process with traditional pharmaceutical excipients and lattice internal structure design. Copyright © 2017. Published by Elsevier B.V.

Compound annotation with real time cellular activity profiles to improve drug discovery.

PubMed

Fang, Ye

2016-01-01

In the past decade, a range of innovative strategies have been developed to improve the productivity of pharmaceutical research and development. In particular, compound annotation, combined with informatics, has provided unprecedented opportunities for drug discovery. In this review, a literature search from 2000 to 2015 was conducted to provide an overview of the compound annotation approaches currently used in drug discovery. Based on this, a framework related to a compound annotation approach using real-time cellular activity profiles for probe, drug, and biology discovery is proposed. Compound annotation with chemical structure, drug-like properties, bioactivities, genome-wide effects, clinical phenotypes, and textural abstracts has received significant attention in early drug discovery. However, these annotations are mostly associated with endpoint results. Advances in assay techniques have made it possible to obtain real-time cellular activity profiles of drug molecules under different phenotypes, so it is possible to generate compound annotation with real-time cellular activity profiles. Combining compound annotation with informatics, such as similarity analysis, presents a good opportunity to improve the rate of discovery of novel drugs and probes, and enhance our understanding of the underlying biology.

Development of self-assembled molecular structures on polymeric surfaces and their applications as ultrasonically responsive barrier coatings for on-demand, pulsatile drug delivery

NASA Astrophysics Data System (ADS)

Kwok, Connie Sau-Kuen

Nature in the form of DNA, proteins, and cells has the remarkable ability to interact with its environment by processing biological information through specific molecular recognition at the interface. As such, materials that are capable of triggering an appropriate biological response need to be engineered at the biomaterial surface. Chemically and structurally well-defined self-assembled monolayers (SAMs), biomimetics of the lipid bilayer in cell membranes, have been created and studied mostly on rigid metallic surfaces. This dissertation is motivated by the lack of methods to generate a molecularly designed surface for biomedical polymers and thus provides an enabling technology to engineer a polymeric surface precisely at a molecular and cellular level. To take this innovation one step further, we demonstrated that such self-assembled molecular structure coated on drug-containing polymeric devices could act as a stimulus-responsive barrier for controlled drug delivery. A simple, one-step procedure for generating ordered, crystalline methylene chains on polymeric surfaces via urethane linkages was successfully developed. The self-assemblies and molecular structures of these crystalline methylene chains are comparable to the SAM model surfaces, as evidenced by various surface characterization techniques (XPS, TOF-SIMS, and FTIR-ATR). For the first time, these self-assembled molecular structures are shown to function collectively as an ultrasound-responsive barrier membrane for pulsatile drug delivery, including delivery of low-molecular-weight ciprofloxacin and high-molecular-weight insulin. Encouraging results, based on the insulin-activated deoxyglucose uptakes in adipocytes, indicate that the released insulin remained biologically active. Both chemical and acoustic analyses suggest that the ultrasound-assisted release mechanism is primarily induced by transient cavitation, which causes temporary disruption of the self-assembled overlayer, and thus allows temporal release of the encapsulated drugs. In addition to acoustic energy, self-assembled surfaces experience order-disorder transition and have a transition temperature higher than body temperature if longer alkyl chains (C18) are used. The C18-assembled surface barrier membrane exhibits a relatively superior impermeable coating than the shorter C12 chains. The versatility of derivatizing the terminal groups of the self-assembled molecular structures is illustrated by attaching poly (ethyleneoxide) oligomers to the alkyl chains to minimize nonspecific protein adsorption. This study lays an important foundation for future work in conjugating other biomolecules to develop surface-based diagnostics and biomaterials. With much success, this original research work of forming self-assembled crystalline structures on synthetic materials still allows for numerous opportunities for new applications and possibly even more new discoveries.

Analytical surveillance of emerging drugs of abuse and drug formulations

PubMed Central

Thomas, Brian F.; Pollard, Gerald T.; Grabenauer, Megan

2012-01-01

Uncontrolled recreational drugs are proliferating in number and variety. Effects of long-term use are unknown, and regulation is problematic, as efforts to control one chemical often lead to several other structural analogs. Advanced analytical instrumentation and methods are continuing to be developed to identify drugs, chemical constituents of products, and drug substances and metabolites in biological fluids. Several mass spectrometry based approaches appear promising, particularly those that involve high resolution chromatographic and mass spectrometric methods that allow unbiased data acquisition and sophisticated data interrogation. Several of these techniques are shown to facilitate both targeted and broad spectrum analysis, which is often of particular benefit when dealing with misleadingly labeled products or assessing a biological matrix for illicit drugs and metabolites. The development and application of novel analytical approaches such as these will help to assess the nature and degree of exposure and risk and, where necessary, inform forensics and facilitate implementation of specific regulation and control measures. PMID:23154240

Development of a Terpenoid Alkaloid-like Compound Library Based on the Humulene Skeleton.

PubMed

Kikuchi, Haruhisa; Nishimura, Takehiro; Kwon, Eunsang; Kawai, Junya; Oshima, Yoshiteru

2016-10-24

Many natural terpenoid alkaloid conjugates show biological activity because their structures contain both sp 3 -rich terpenoid scaffolds and nitrogen-containing alkaloid scaffolds. However, their biosynthesis utilizes a limited set of compounds as sources of the terpenoid moiety. The production of terpenoid alkaloids containing various types of terpenoid moiety may provide useful, chemically diverse compound libraries for drug discovery. Herein, we report the construction of a library of terpenoid alkaloid-like compounds based on Lewis-acid-catalyzed transannulation of humulene diepoxide and subsequent sequential olefin metathesis. Cheminformatic analysis quantitatively showed that the synthesized terpenoid alkaloid-like compound library has a high level of three-dimensional-shape diversity. Extensive pharmacological screening of the library has led to the identification of promising compounds for the development of antihypolipidemic drugs. Therefore, the synthesis of terpenoid alkaloid-like compound libraries based on humulene is well suited to drug discovery. Synthesis of terpenoid alkaloid-like compounds based on several natural terpenoids is an effective strategy for producing chemically diverse libraries. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Collaborative Core Research Program for Chemical-Biological Warfare Defense

DTIC Science & Technology

2015-01-04

Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that

Discovery of novel dengue virus NS5 methyltransferase non-nucleoside inhibitors by fragment-based drug design.

PubMed

Benmansour, Fatiha; Trist, Iuni; Coutard, Bruno; Decroly, Etienne; Querat, Gilles; Brancale, Andrea; Barral, Karine

2017-01-05

With the aim to help drug discovery against dengue virus (DENV), a fragment-based drug design approach was applied to identify ligands targeting a main component of DENV replication complex: the NS5 AdoMet-dependent mRNA methyltransferase (MTase) domain, playing an essential role in the RNA capping process. Herein, we describe the identification of new inhibitors developed using fragment-based, structure-guided linking and optimization techniques. Thermal-shift assay followed by a fragment-based X-ray crystallographic screening lead to the identification of three fragment hits binding DENV MTase. We considered linking two of them, which bind to proximal sites of the AdoMet binding pocket, in order to improve their potency. X-ray crystallographic structures and computational docking were used to guide the fragment linking, ultimately leading to novel series of non-nucleoside inhibitors of flavivirus MTase, respectively N-phenyl-[(phenylcarbamoyl)amino]benzene-1-sulfonamide and phenyl [(phenylcarbamoyl)amino]benzene-1-sulfonate derivatives, that show a 10-100-fold stronger inhibition of 2'-O-MTase activity compared to the initial fragments. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Nanosized ethosomes-based hydrogel formulations of methoxsalen for enhanced topical delivery against vitiligo: formulation optimization, in vitro evaluation and preclinical assessment.

PubMed

Garg, Bhawna Jain; Garg, Neeraj K; Beg, Sarwar; Singh, Bhupinder; Katare, Om Prakash

2016-01-01

The present investigation aimed for the development and characterization of ethosomes-based hydrogel formulations of methoxsalen for enhanced topical delivery and effective treatment against vitiligo. The ethosomes were prepared by central composite design (CCD) and characterized for various quality attributes like vesicle shape, size, zeta potential, lamellarity, drug entrapment and drug leaching. The optimized ethosomes were subsequently incorporated int Carbopol® 934 gel and characterized for drug content, rheological behavior, texture profile, in vitro release, ex vivo skin permeation and retention, skin photosensitization and histopathological examination. Ethosomes were found to be spherical and multilamellar in structures having nanometric size range with narrow size distribution, and high encapsulation efficiency. Ethosomal formulations showed significant skin permeation and accumulation in the epidermal and dermal layers. The fluorescence microscopy study using 123 Rhodamine exhibited enhanced permeation of the drug-loaded ethosomes in the deeper layers of skin. Also, the developed formulation showed insignificant phototoxicity and erythema vis-à-vis the conventional cream. The results were cross-validated using histopathological examination of skin segments. In a nutshell, the ethosomes-based hydrogel formulation was found to be a promising drug delivery system demonstrating enhanced percutaneous penetration of methoxsalen with reduced phototoxicity and erythema, thus leading to improved patient compliance for the treatment against vitiligo.

Liquid Crystalline Systems Based on Glyceryl Monooleate and Penetration Enhancers for Skin Delivery of Celecoxib: Characterization, In Vitro Drug Release, and In Vivo Studies.

PubMed

Dante, Mariane de Cássia Lima; Borgheti-Cardoso, Livia Neves; Fantini, Marcia Carvalho de Abreu; Praça, Fabíola Silva Garcia; Medina, Wanessa Silva Garcia; Pierre, Maria Bernadete Riemma; Lara, Marilisa Guimarães

2018-03-01

Celecoxib (CXB) is a widely used anti-inflammatory drug that also acts as a chemopreventive agent against several types of cancer, including skin cancer. As the long-term oral administration of CXB has been associated with severe side effects, the skin delivery of this drug represents a promising alternative for the treatment of skin inflammatory conditions and chemoprevention of skin cancer. We prepared and characterized liquid crystalline systems based on glyceryl monooleate and water containing penetration enhancers which were primarily designed to promote skin delivery of CXB. Analysis of their phase behavior revealed the formation of cubic and hexagonal phases depending on the systems' composition. The systems' structure and composition markedly affected the in vitro CXB release profile. Oleic acid reduced CXB release rate, but association oleic acid/propylene glycol increased the drug release rate. The developed systems significantly reduced inflammation in an aerosil-induced rat paw edema model. The systems' composition and liquid crystalline structure influenced their anti-inflammatory potency. Cubic phase systems containing oleic acid/propylene glycol association reduced edema in a sustained manner, indicating that they modulate CXB release and permeation. Our findings demonstrate that the developed liquid crystalline systems are potential carriers for the skin delivery of CXB. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

The war against influenza: discovery and development of sialidase inhibitors.

PubMed

von Itzstein, Mark

2007-12-01

The threat of a major human influenza pandemic, in particular from highly aggressive strains such as avian H5N1, has emphasized the need for therapeutic strategies to combat these pathogens. At present, two inhibitors of sialidase (also known as neuraminidase), a viral enzyme that has a key role in the life cycle of influenza viruses, would be the mainstay of pharmacological strategies in the event of such a pandemic. This article provides a historical perspective on the discovery and development of these drugs--zanamivir and oseltamivir--and highlights the value of structure-based drug design in this process.

QSAR of phytochemicals for the design of better drugs.

PubMed

Kar, Supratik; Roy, Kunal

2012-10-01

Phytochemicals have been the single most prolific source of leads for the development of new drug entities from the dawn of the drug discovery. They cover a wide range of therapeutic indications with a great diversity of chemical structures. The research fraternity still believes in exploring the phytochemicals for new drug discovery. Application of molecular biological techniques has increased the availability of novel compounds that can be conveniently isolated from natural sources. Combinatorial chemistry approaches are being applied based on phytochemical scaffolds to create screening libraries that closely resemble drug-like compounds. In silico techniques like quantitative structure-activity relationships (QSAR), pharmacophore and virtual screening are playing crucial and rate accelerating steps for the better drug design in modern era. QSAR models of different classes of phytochemicals covering different therapeutic areas are thoroughly discussed in the review. Further, the authors have enlisted all the available phytochemical databases for the convenience of researchers working in the area. This review justifies the need to develop more QSAR models for the design of better drugs from phytochemicals. Technical drawbacks associated with phytochemical research have been lessened, and there are better opportunities to explore the biological activity of previously inaccessible sources of phytochemicals although there is still the need to reduce the time and cost involvement in such exercise. The future possibilities for the integration of ethnopharmacology with QSAR, place us at an exciting stage that will allow us to explore plant sources worldwide and design better drugs.

Editorial: Current status and perspective on drug targets in tubercle bacilli and drug design of antituberculous agents based on structure-activity relationship.

PubMed

Tomioka, Haruaki

2014-01-01

Worldwide, tuberculosis (TB) remains the most frequent and important infectious disease causing morbidity and death. However, the development of new drugs for the treatment and prophylaxis of TB, particularly those truly active against dormant and persistent types of tubercle bacilli, has been slow, although some promising drugs, such as diarylquinoline TMC207, nitroimidazopyran PA-824, nitroimidazo-oxazole Delamanid (OPC-67683), oxazolidinone PNU-100480, ethylene diamine SQ-109, and pyrrole derivative LL3858, are currently under phase 1 to 3 clinical trials. Therefore, novel types of antituberculous drug, which act on unique drug targets in Mycobacterium tuberculosis (MTB) pathogens, particularly drug targets related to the establishment of mycobacterial dormancy in the host's macrophages, are urgently needed. In this context, it should be noted that current anti-TB drugs mostly target the metabolic reactions and proteins which are essential for the growth of MTB in extracellular milieus. It may also be promising to develop another type of drug that exerts an inhibitory action against bacterial virulence factors which cross-talk and interfere with signaling pathways of MTB-infected immunocompetent host cells, such as lymphocytes, macrophages, and NK cells, thereby changing the intracellular milieus that are favorable to intramacrophage survival and the growth of infected bacilli. This special issue contains ten review articles, dealing with recent approaches to identify and establish novel drug targets in MTB for the development of new and unique antitubercular drugs, including those related to mycobacterial dormancy and crosstalk with cellular signaling pathways. In addition, this special issue contains some review papers with special reference to the drug design based on quantitative structure-activity relationship (QSAR) analysis, especially three-dimensional (3D)-QSAR. New, critical information on the entire genome of MTB and mycobacterial virulence genes is promoting the elucidation of the molecular structures of drug targets in MTB, and are consequently markedly useful for the design of new, promising antituberculous drugs using QSAR techniques. In this issue, we review the following areas. Firstly, Dr. Li M. Fu reviews the perspective that combines machine learning and genomics for drug discovery in tuberculosis, in relation to the problem that the exhaustive search for useful drug targets over the entire MTB genome would not be as productive as expected in practice [1]. Secondly, the review article by Drs. R. S. Chauhan. S. K. Chanumolu, C. Rout, and R. Shrivastava focuses on analysis of the current state of MTB genomic resources, host-pathogen interaction studies in the context of mycobacterial persistence, and drug target discovery based on the utilization of computational tools and metabolic network analyses [2]. Thirdly, Drs. Daria Bottai, Agnese Serafini, Alessandro Cascioferro, Roland Brosch, and Riccardo Manganelli review the current knowledge on MTB T7SS/ESX secretion systems and their impact on MTB physiology and virulence, and the possible approaches to develop T7SS/ESX inhibitors [3]. Fourthly, Drs. E. Jeffrey North, Mary Jackson, and Richard E. Lee review and analyze new and emerging inhibitors of the mycolic acid biosynthetic pathway, including mycobacterial enzymes for fatty acid synthesis, mycolic acid-modifying enzymes, fatty acid-activating and -condensing enzymes, transporters, and transferases, that have been discovered in the post-genomic era of tuberculosis drug discovery [4]. Fifthly, Drs. Katarina Mikusova, Vadim Makarov, and Joao Neres review the mycobacterial enzyme DprE1, which catalyzes a unique epimerization reaction in the biosynthesis of decaprenylphosphoryl arabinose, a single donor of the arabinosyl residue for the build-up of arabinans, one of the mycobacterial cell wall components, as an important drug target especially for the development of benzothiazinones [5]. Sixthly, I review the present status of global research on novel drug targets related to the Toll-like receptor in the MTB pathogen, with special reference to mycobacterial virulence factors that cross-talk and interfere with signaling pathways of host macrophages [6]. The following four review articles deal with drug design of novel anti-TB agents employing QSAR techniques. Firstly, Drs. Nidhi and Mohammad Imran Siddiqi review 2D and 3D QSAR approaches and the recent trends of these methods integrated with virtual screening using the 3D pharmacophore and molecular docking approaches for the identification and design of novel antituberculous agents, by presenting a comprehensive overview of QSAR studies reported for newer antituberculous agents [7]. Secondly, Drs. Filomena Martins, Cristina Ventura, Susana Santos, and Miguel Viveiros review the current status of different QSAR-based strategies for the design of novel anti-TB drugs based upon the most active anti-TB agent, isoniazid, from the viewpoint of the development of promising derivatives that are active against isoniazid- resistant strains with katG mutations [8]. Thirdly, Drs. Sanchaita Rajkhowa and Ramesh C. Deka review current studies concerning 2D and 3D QSAR models that contain density-functional theory (DFT)-based descriptors as their parameters [9]. Notably, DFT-based descriptors such as atomic charges, molecular orbital energies, frontier orbital densities, and atom-atom polarizabilities are very useful in predicting the reactivity of atoms in molecules. Fourthly, Drs. Renata V. Bueno, Rodolpho C. Braga, Natanael D. Segretti, Elizabeth I. Ferreira, Gustavo H. G. Trossini, and Carolina H. Andrade review the current progress and applications of QSAR analysis for the discovery of innovative tuberculostatic agents as inhibitors of ribonucleotide reductase, DNA gyrase, ATP synthase, and thymidylate kinase enzymes, highlighting present challenges and new opportunities in TB drug design [10]. The aim of this issue is to address the future prospects for the development of new antituberculous drugs. There are a number of difficulties in computational drug-design for the development of new drug formulations with potential antimycobacterial effects, especially therapeutic and prophylactic efficacy against infection due to dormant-type MTB pathogens. In addition, it should be emphasized that the most urgent goal of TB chemotherapy is develop highly active, low-cost drugs which can be used not only in industrialized but also in developing countries, because most global TB incidence occurs in the latter. I am sincerely grateful to the individuals who contributed to this work. All authors are experts in their fields and they made earnest efforts to perform these in-depth reviews. I thank them all.

Medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and invention of boron tracedrugs as innovative future-architectural drugs.

PubMed

Hori, Hitoshi; Uto, Yoshihiro; Nakata, Eiji

2010-09-01

We describe herein for the first time our medicinal electronomics bricolage design of hypoxia-targeting antineoplastic drugs and boron tracedrugs as newly emerging drug classes. A new area of antineoplastic drugs and treatments has recently focused on neoplastic cells of the tumor environment/microenvironment involving accessory cells. This tumor hypoxic environment is now considered as a major factor that influences not only the response to antineoplastic therapies but also the potential for malignant progression and metastasis. We review our medicinal electronomics bricolage design of hypoxia-targeting drugs, antiangiogenic hypoxic cell radiosensitizers, sugar-hybrid hypoxic cell radiosensitizers, and hypoxia-targeting 10B delivery agents, in which we design drug candidates based on their electronic structures obtained by molecular orbital calculations, not based solely on pharmacophore development. These drugs include an antiangiogenic hypoxic cell radiosensitizer TX-2036, a sugar-hybrid hypoxic cell radiosensitizer TX-2244, new hypoxia-targeting indoleamine 2,3-dioxygenase (IDO) inhibitors, and a hypoxia-targeting BNCT agent, BSH (sodium borocaptate-10B)-hypoxic cytotoxin tirapazamine (TPZ) hybrid drug TX-2100. We then discuss the concept of boron tracedrugs as a new drug class having broad potential in many areas.

Uniform Surface Modification of 3D Bioglass®-Based Scaffolds with Mesoporous Silica Particles (MCM-41) for Enhancing Drug Delivery Capability

PubMed Central

Boccardi, Elena; Philippart, Anahí; Juhasz-Bortuzzo, Judith A.; Beltrán, Ana M.; Novajra, Giorgia; Vitale-Brovarone, Chiara; Spiecker, Erdmann; Boccaccini, Aldo R.

2015-01-01

The design and characterization of a new family of multifunctional scaffolds based on bioactive glass (BG) of 45S5 composition for bone tissue engineering and drug delivery applications are presented. These BG-based scaffolds are developed via a replication method of polyurethane packaging foam. In order to increase the therapeutic functionality, the scaffolds were coated with mesoporous silica particles (MCM-41), which act as an in situ drug delivery system. These sub-micron spheres are characterized by large surface area and pore volume with a narrow pore diameter distribution. The solution used for the synthesis of the silica mesoporous particles was designed to obtain a high-ordered mesoporous structure and spherical shape – both are key factors for achieving the desired controlled drug release. The MCM-41 particles were synthesized directly inside the BG-based scaffolds, and the drug-release capability of this combined system was evaluated. Moreover, the effect of MCM-41 particle coating on the bioactivity of the BG-based scaffolds was assessed. The results indicate that it is possible to obtain a multifunctional scaffold system characterized by high and interconnected porosity, high bioactivity, and sustained drug delivery capability. PMID:26594642

Bioinformatics and variability in drug response: a protein structural perspective

PubMed Central

Lahti, Jennifer L.; Tang, Grace W.; Capriotti, Emidio; Liu, Tianyun; Altman, Russ B.

2012-01-01

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk–benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein–drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein–drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants. PMID:22552919

Deconstructing the Drug Development Process: The New Face of Innovation

PubMed Central

Kaitin, KI

2010-01-01

Forged in the early 1960s, the paradigm for pharmaceutical innovation has remained virtually unchanged for nearly 50 years. During a period when most other research-based industries have made frequent and often sweeping modifications to their R&D processes, the pharmaceutical sector continues to utilize a drug development process that is slow, inefficient, risky, and expensive. Few who work in or follow the activities of the pharmaceutical industry question whether change is coming. They know that the pharmaceutical sector, as currently structured, is unable to deliver enough new products to market to generate revenues sufficient to sustain its own growth. Nearly all major drug developers are critically examining current R&D practices and, in some cases, considering a radical overhaul of their R&D models. But key questions remain. What will the landscape for pharmaceutical innovation look like in the future? And, who will develop tomorrow’s medicines? PMID:20130565

Experimental design-based strategy for the simulation of complex gaseous mixture spectra to detect drug precursors

NASA Astrophysics Data System (ADS)

Calderisi, Marco; Ulrici, Alessandro; Pigani, Laura; Secchi, Alberto; Seeber, Renato

2012-09-01

The EU FP7 project CUSTOM (Drugs and Precursor Sensing by Complementing Low Cost Multiple Techniques) aims at developing a new sensing system for the detection of drug precursors in gaseous samples, which includes an External Cavity-Quantum Cascade Laser Photo-Acoustic Sensor (EC-QCLPAS) that is in the final step of realisation. Thus, a simulation based on FT-IR literature spectra has been accomplished, where the development of a proper strategy for the design of the composition of the environment, as much as possible realistic and representative of different scenarios, is of key importance. To this aim, an approach based on the combination of signal processing and experimental design techniques has been developed. The gaseous mixtures were built by adding the considered 4 drug precursor (target) species to the gases typically found in atmosphere, taking also into account possible interfering species. These last chemicals were selected considering custom environments (20 interfering chemical species), whose concentrations have been inferred from literature data. The spectra were first denoised by means of a Fast Wavelet Transform-based algorithm; then, a procedure based on a sigmoidal transfer function was developed to multiply the pure components spectra by the respective concentration values, in a way to correctly preserve background intensity and shape, and to operate only on the absorption bands. The noise structure of the EC-QCLPAS was studied using sample spectra measured with a prototype instrument, and added to the simulated mixtures. Finally a matrix containing 5000 simulated spectra of gaseous mixtures was built up.

Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods

PubMed Central

2015-01-01

Background Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. Methods In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. Results We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Conclusions Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy. PMID:26680552

Piloting a 'spatial isolation' index: the built environment and sexual and drug use risks to sex workers.

PubMed

Deering, Kathleen N; Rusch, Melanie; Amram, Ofer; Chettiar, Jill; Nguyen, Paul; Feng, Cindy X; Shannon, Kate

2014-05-01

Employing innovative mapping and spatial analyses of individual and neighbourhood environment data, we examined the social, physical and structural features of overlapping street-based sex work and drug scenes and explored the utility of a 'spatial isolation index' in explaining exchanging sex for drugs and exchanging sex while high. Analyses drew on baseline interview and geographic data (January 2010-October 2011) from a large prospective cohort of street and off-street sex workers (SWs) in Metropolitan Vancouver and external publically-available, neighbourhood environment data. An index measuring 'spatial isolation' was developed from seven indicators measuring features of the built environment within 50m buffers (e.g., industrial or commercial zoning, lighting) surrounding sex work environments. Bivariate and multivariable logistic regression was used to examine associations between the two outcomes (exchanged sex for drugs; exchanged sex while high) and the index, as well as each individual indicator. Of 510 SWs, 328 worked in street-based/outdoor environments (e.g., streets, parks, alleys) and were included in the analyses. In multivariable analysis, increased spatial isolation surrounding street-based/outdoor SWs' main places of servicing clients as measured with the index was significantly associated with exchanging sex for drugs. Exchanging sex for drugs was also significantly positively associated with an indicator of the built environment suggesting greater spatial isolation (increased percent of parks) and negatively associated with those suggesting decreased spatial isolation (increased percent commercial areas, increased count of lighting, increased building footprint). Exchanging sex while high was negatively associated with increased percent of commercial zones but this association was removed when adjusting for police harassment. The results from our exploratory study highlight how built environment shapes risks within overlapping street-based sex work and drug scenes through the development of a novel index comprised of multiple indicators of the built environment available through publicly available data, This study informs the important role that spatially-oriented responses, such as safer-environment interventions, and structural responses, such as decriminalization of sex work can play in improving the health, safety and well-being of SWs. Copyright © 2013 Elsevier B.V. All rights reserved.

Piloting a ‘Spatial Isolation’ Index: The Built Environment and Sexual and Drug Use Risks to Sex Workers

PubMed Central

Deering, Kathleen N; Rusch, Melanie; Amram, Ofer; Chettiar, Jill; Nguyen, Paul; Feng, Cindy X; Shannon, Kate

2014-01-01

Background Employing innovative mapping and spatial analyses of individual and neighborhood environment data, we examined the social, physical and structural features of overlapping street-based sex work and drug scenes and explored the utility of a ‘spatial isolation index’ in explaining exchanging sex for drugs and exchanging sex while high. Methods Analyses drew on baseline interview and geographic data (Jan/10-Oct/11) from a large prospective cohort of street and off-street sex workers (SWs) in Metropolitan Vancouver and external publically-available, neighborhood environment data. An index measuring ‘spatial isolation’ was developed from seven indicators measuring features of the built environment within 50m buffers (e.g. industrial or commercial zoning, lighting) surrounding sex work environments. Bivariate and multivariable logistic regression was used to examine associations between the two outcomes (exchanged sex for drugs; exchanged sex while high) and the index, as well as each individual indicator. Results Of 510 SWs, 328 worked in street-based/outdoor environments (e.g. streets, parks, alleys) and were included in the analyses. In multivariable analysis, increased spatial isolation surrounding street-based/outdoor SWs’ main places of servicing clients as measured with the index was significantly associated with exchanging sex for drugs. Exchanging sex for drugs was also significantly positively associated with an indicator of the built environment suggesting greater spatial isolation (increased percent of parks) and negatively associated with those suggesting decreased spatial isolation (increased percent commercial areas, increased count of lighting, increased building footprint). Exchanging sex while high was negatively associated with increased percent of commercial zones but this association was removed when adjusting for police harassment. Conclusions The results from our exploratory study highlight how built environment shapes risks within overlapping street-based sex work and drug scenes through the development of a novel index comprised of multiple indicators of the built environment available through publicly available data, This study informs the important role that spatially-oriented responses, such as safer-environment interventions, and structural responses, such as decriminalization of sex work can play in improving the health, safety and well-being of SWs. PMID:24433813

The development of a personalized patient education tool for decision making for postmenopausal women with osteoporosis.

PubMed

Hiligsmann, M; Ronda, G; van der Weijden, T; Boonen, A

2016-08-01

A personalized patient education tool for decision making (PET) for postmenopausal women with osteoporosis was developed by means of a systematic development approach. A prototype was constructed and refined by involving various professionals and patients. Professionals and patients expressed a positive attitude towards the use of the PET. The purpose was to systematically develop a paper-based personalized PET to assist postmenopausal women with osteoporosis in selecting a treatment in line with their personal values and preferences. The development of the PET was based on a systematic process including scope, design, development of a prototype, and alpha testing among professionals and patients by semi-structured interviews. The design and development resulted in a four-page PET prototype together with a one-page fact sheet of the different drug options. The prototype PET provided the personal risk factors, the estimated individualized risk for a future major osteoporotic fracture and potential reduction with drugs, and a summary of advantages and disadvantages whether or not to start drugs. The drug fact sheet presents five attributes of seven drugs in a tabular format. The alpha testing with professionals resulted in some adaptations, e.g., inclusion of the possibility to calculate fracture risk based on various individual risk scoring methods. Important results from the alpha testing with patients were differences in the fracture risk percentage which was seen as worthwhile to start drugs, the importance of an overview of side effects, and of the timing of the PET into the patient pathway. All women indicated that the PET could be helpful for their decision to select a treatment. Physicians and patients expressed a positive attitude towards the use of the proposed PET. Further research would be needed to test the effects of the PET on feasibility in clinical workflow and on patient outcomes.

Structure-based drug discovery for combating influenza virus by targeting the PA-PB1 interaction.

PubMed

Watanabe, Ken; Ishikawa, Takeshi; Otaki, Hiroki; Mizuta, Satoshi; Hamada, Tsuyoshi; Nakagaki, Takehiro; Ishibashi, Daisuke; Urata, Shuzo; Yasuda, Jiro; Tanaka, Yoshimasa; Nishida, Noriyuki

2017-08-25

Influenza virus infections are serious public health concerns throughout the world. The development of compounds with novel mechanisms of action is urgently required due to the emergence of viruses with resistance to the currently-approved anti-influenza viral drugs. We performed in silico screening using a structure-based drug discovery algorithm called Nagasaki University Docking Engine (NUDE), which is optimised for a GPU-based supercomputer (DEstination for Gpu Intensive MAchine; DEGIMA), by targeting influenza viral PA protein. The compounds selected by NUDE were tested for anti-influenza virus activity using a cell-based assay. The most potent compound, designated as PA-49, is a medium-sized quinolinone derivative bearing a tetrazole moiety, and it inhibited the replication of influenza virus A/WSN/33 at a half maximal inhibitory concentration of 0.47 μM. PA-49 has the ability to bind PA and its anti-influenza activity was promising against various influenza strains, including a clinical isolate of A(H1N1)pdm09 and type B viruses. The docking simulation suggested that PA-49 interrupts the PA-PB1 interface where important amino acids are mostly conserved in the virus strains tested, suggesting the strain independent utility. Because our NUDE/DEGIMA system is rapid and efficient, it may help effective drug discovery against the influenza virus and other emerging viruses.

The SGC beyond structural genomics: redefining the role of 3D structures by coupling genomic stratification with fragment-based discovery.

PubMed

Bradley, Anthony R; Echalier, Aude; Fairhead, Michael; Strain-Damerell, Claire; Brennan, Paul; Bullock, Alex N; Burgess-Brown, Nicola A; Carpenter, Elisabeth P; Gileadi, Opher; Marsden, Brian D; Lee, Wen Hwa; Yue, Wyatt; Bountra, Chas; von Delft, Frank

2017-11-08

The ongoing explosion in genomics data has long since outpaced the capacity of conventional biochemical methodology to verify the large number of hypotheses that emerge from the analysis of such data. In contrast, it is still a gold-standard for early phenotypic validation towards small-molecule drug discovery to use probe molecules (or tool compounds), notwithstanding the difficulty and cost of generating them. Rational structure-based approaches to ligand discovery have long promised the efficiencies needed to close this divergence; in practice, however, this promise remains largely unfulfilled, for a host of well-rehearsed reasons and despite the huge technical advances spearheaded by the structural genomics initiatives of the noughties. Therefore the current, fourth funding phase of the Structural Genomics Consortium (SGC), building on its extensive experience in structural biology of novel targets and design of protein inhibitors, seeks to redefine what it means to do structural biology for drug discovery. We developed the concept of a Target Enabling Package (TEP) that provides, through reagents, assays and data, the missing link between genetic disease linkage and the development of usefully potent compounds. There are multiple prongs to the ambition: rigorously assessing targets' genetic disease linkages through crowdsourcing to a network of collaborating experts; establishing a systematic approach to generate the protocols and data that comprise each target's TEP; developing new, X-ray-based fragment technologies for generating high quality chemical matter quickly and cheaply; and exploiting a stringently open access model to build multidisciplinary partnerships throughout academia and industry. By learning how to scale these approaches, the SGC aims to make structures finally serve genomics, as originally intended, and demonstrate how 3D structures systematically allow new modes of druggability to be discovered for whole classes of targets. © 2017 The Author(s).

Molecular design for enhancement of ocular penetration.

PubMed

Shirasaki, Yoshihisa

2008-07-01

Over the past two decades, many oral drugs have been designed in consideration of physicochemical properties to attain optimal pharmacokinetic properties. This strategy significantly reduced attrition in drug development owing to inadequate pharmacokinetics during the last decade. On the other hand, most ophthalmic drugs are generated from reformulation of other therapeutic dosage forms. Therefore, the modification of formulations has been used mainly as the approach to improve ocular pharmacokinetics. However, to maximize ocular pharmacokinetic properties, a specific molecular design for ocular drug is preferable. Passive diffusion of drugs across the cornea membranes requires appropriate lipophilicity and aqueous solubility. Improvement of such physicochemical properties has been achieved by structure optimization or prodrug approaches. This review discusses the current knowledge about ophthalmic drugs adapted from systemic drugs and molecular design for ocular drugs. I propose the approaches for molecular design to obtain the optimal ocular penetration into anterior segment based on published studies to date.

On the exfoliating polymeric cellular dosage forms for immediate drug release.

PubMed

Blaesi, Aron H; Saka, Nannaji

2016-06-01

The most prevalent pharmaceutical dosage forms at present-the oral immediate-release tablets and capsules-are granular solids. Though effective in releasing drug rapidly, development and manufacture of such dosage forms are fraught with difficulties inherent to particulate processing. Predictable dosage form manufacture could be achieved by liquid-based processing, but cast solid dosage forms are not suitable for immediate drug release due to their resistance to fluid percolation. To overcome this limitation, we have recently introduced cellular dosage forms that can be readily prepared from polymeric melts. It has been shown that open-cell structures comprising polyethylene glycol 8000 (PEG 8k) excipient and a drug exfoliate upon immersion in a dissolution medium. The drug is then released rapidly due to the large specific surface area of the exfoliations. In this work, we vary the molecular weight of the PEG excipient and investigate its effect on the drug release kinetics of structures with predominantly open-cell topology. We demonstrate that the exfoliation rate decreases substantially if the excipient molecular weight is increased from 12 to 100kg/mol, which causes the drug dissolution time to increase by more than a factor of ten. A model is then developed to elucidate the exfoliation behavior of cellular structures. Diverse transport processes are considered: percolation due to capillarity, diffusion of dissolution medium through the cell walls, and viscous flow of the saturated excipient. It is found that the lower exfoliation rate and the longer dissolution time of the dosage forms with higher excipient molecular weight are primarily due to the greater viscosity of the cell walls after fluid penetration. Copyright © 2016 Elsevier B.V. All rights reserved.

The multiple roles of computational chemistry in fragment-based drug design

NASA Astrophysics Data System (ADS)

Law, Richard; Barker, Oliver; Barker, John J.; Hesterkamp, Thomas; Godemann, Robert; Andersen, Ole; Fryatt, Tara; Courtney, Steve; Hallett, Dave; Whittaker, Mark

2009-08-01

Fragment-based drug discovery (FBDD) represents a change in strategy from the screening of molecules with higher molecular weights and physical properties more akin to fully drug-like compounds, to the screening of smaller, less complex molecules. This is because it has been recognised that fragment hit molecules can be efficiently grown and optimised into leads, particularly after the binding mode to the target protein has been first determined by 3D structural elucidation, e.g. by NMR or X-ray crystallography. Several studies have shown that medicinal chemistry optimisation of an already drug-like hit or lead compound can result in a final compound with too high molecular weight and lipophilicity. The evolution of a lower molecular weight fragment hit therefore represents an attractive alternative approach to optimisation as it allows better control of compound properties. Computational chemistry can play an important role both prior to a fragment screen, in producing a target focussed fragment library, and post-screening in the evolution of a drug-like molecule from a fragment hit, both with and without the available fragment-target co-complex structure. We will review many of the current developments in the area and illustrate with some recent examples from successful FBDD discovery projects that we have conducted.

Ab initio design of drug carriers for zoledronate guest molecule using phosphonated and sulfonated calix[4]arene and calix[4]resorcinarene host molecules

NASA Astrophysics Data System (ADS)

Jang, Yong-Man; Yu, Chol-Jun; Kim, Jin-Song; Kim, Song-Un

2018-04-01

Monomolecular drug carriers based on calix[n]-arenes and -resorcinarenes containing the interior cavity can enhance the affinity and specificity of the osteoporosis inhibitor drug zoledronate (ZOD). In this work we investigate the suitability of nine different calix[4]-arenes and -resorcinarenes based macrocycles as hosts for the ZOD guest molecule by conducting {\\it ab initio} density functional theory calculations for structures and energetics of eighteen different host-guest complexes. For the optimized molecular structures of the free, phosphonated, sulfonated calix[4]-arenes and -resorcinarenes, the geometric sizes of their interior cavities are measured and compared with those of the host-guest complexes in order to check the appropriateness for host-guest complex formation. Our calculations of binding energies indicate that in gaseous states some of the complexes might be unstable but in aqueous states almost all of the complexes can be formed spontaneously. Of the two different docking ways, the insertion of ZOD with the \\ce{P-C-P} branch into the cavity of host is easier than that with the nitrogen containing heterocycle of ZOD. The work will open a way for developing effective drug delivering systems for the ZOD drug and promote experimentalists to synthesize them.

Structural basis of RND-type multidrug exporters

PubMed Central

Yamaguchi, Akihito; Nakashima, Ryosuke; Sakurai, Keisuke

2015-01-01

Bacterial multidrug exporters are intrinsic membrane transporters that act as cellular self-defense mechanism. The most notable characteristics of multidrug exporters is that they export a wide range of drugs and toxic compounds. The overexpression of these exporters causes multidrug resistance. Multidrug-resistant pathogens have become a serious problem in modern chemotherapy. Over the past decade, investigations into the structure of bacterial multidrug exporters have revealed the multidrug recognition and export mechanisms. In this review, we primarily discuss RND-type multidrug exporters particularly AcrAB-TolC, major drug exporter in Gram-negative bacteria. RND-type drug exporters are tripartite complexes comprising a cell membrane transporter, an outer membrane channel and an adaptor protein. Cell membrane transporters and outer membrane channels are homo-trimers; however, there is no consensus on the number of adaptor proteins in these tripartite complexes. The three monomers of a cell membrane transporter have varying conformations (access, binding, and extrusion) during transport. Drugs are exported following an ordered conformational change in these three monomers, through a functional rotation mechanism coupled with the proton relay cycle in ion pairs, which is driven by proton translocation. Multidrug recognition is based on a multisite drug-binding mechanism, in which two voluminous multidrug-binding pockets in cell membrane exporters recognize a wide range of substrates as a result of permutations at numerous binding sites that are specific for the partial structures of substrate molecules. The voluminous multidrug-binding pocket may have numerous binding sites even for a single substrate, suggesting that substrates may move between binding sites during transport, an idea named as multisite-drug-oscillation hypothesis. This hypothesis is consistent with the apparently broad substrate specificity of cell membrane exporters and their highly efficient ejection of drugs from the cell. Substrates are transported through dual multidrug-binding pockets via the peristaltic motion of the substrate translocation channel. Although there are no clinically available inhibitors of bacterial multidrug exporters, efforts to develop inhibitors based on structural information are underway. PMID:25941524

Structural basis of RND-type multidrug exporters.

PubMed

Yamaguchi, Akihito; Nakashima, Ryosuke; Sakurai, Keisuke

2015-01-01

Bacterial multidrug exporters are intrinsic membrane transporters that act as cellular self-defense mechanism. The most notable characteristics of multidrug exporters is that they export a wide range of drugs and toxic compounds. The overexpression of these exporters causes multidrug resistance. Multidrug-resistant pathogens have become a serious problem in modern chemotherapy. Over the past decade, investigations into the structure of bacterial multidrug exporters have revealed the multidrug recognition and export mechanisms. In this review, we primarily discuss RND-type multidrug exporters particularly AcrAB-TolC, major drug exporter in Gram-negative bacteria. RND-type drug exporters are tripartite complexes comprising a cell membrane transporter, an outer membrane channel and an adaptor protein. Cell membrane transporters and outer membrane channels are homo-trimers; however, there is no consensus on the number of adaptor proteins in these tripartite complexes. The three monomers of a cell membrane transporter have varying conformations (access, binding, and extrusion) during transport. Drugs are exported following an ordered conformational change in these three monomers, through a functional rotation mechanism coupled with the proton relay cycle in ion pairs, which is driven by proton translocation. Multidrug recognition is based on a multisite drug-binding mechanism, in which two voluminous multidrug-binding pockets in cell membrane exporters recognize a wide range of substrates as a result of permutations at numerous binding sites that are specific for the partial structures of substrate molecules. The voluminous multidrug-binding pocket may have numerous binding sites even for a single substrate, suggesting that substrates may move between binding sites during transport, an idea named as multisite-drug-oscillation hypothesis. This hypothesis is consistent with the apparently broad substrate specificity of cell membrane exporters and their highly efficient ejection of drugs from the cell. Substrates are transported through dual multidrug-binding pockets via the peristaltic motion of the substrate translocation channel. Although there are no clinically available inhibitors of bacterial multidrug exporters, efforts to develop inhibitors based on structural information are underway.

The application of structure-based assessment to support safety and chemistry diligence to manage genotoxic impurities in active pharmaceutical ingredients during drug development.

PubMed

Dobo, Krista L; Greene, Nigel; Cyr, Michelle O; Caron, Stéphane; Ku, Warren W

2006-04-01

Starting materials and intermediates used to synthesize pharmaceuticals are reactive in nature and may be present as impurities in the active pharmaceutical ingredient (API) used for preclinical safety studies and clinical trials. Furthermore, starting materials and intermediates may be known or suspected mutagens and/or carcinogens. Therefore, during drug development due diligence need be applied from two perspectives (1) to understand potential mutagenic and carcinogenic risks associated with compounds used for synthesis and (2) to understand the capability of synthetic processes to control genotoxic impurities in the API. Recently, a task force comprised of experts from pharmaceutical industry proposed guidance, with recommendations for classification, testing, qualification and assessing risk of genotoxic impurities. In our experience the proposed structure-based classification, has differentiated 75% of starting materials and intermediates as mutagenic and non-mutagenic with high concordance (92%) when compared with Ames results. Structure-based assessment has been used to identify genotoxic hazards, and prompted evaluation of fate of genotoxic impurities in API. These two assessments (safety and chemistry) culminate in identification of genotoxic impurities known or suspected to exceed acceptable levels in API, thereby triggering actions needed to assure appropriate control and measurement methods are in place. Hypothetical case studies are presented demonstrating this multi-disciplinary approach.

Exploring the status of retail private drug shops in Bangladesh and action points for developing an accredited drug shop model: a facility based cross-sectional study.

PubMed

Ahmed, Syed Masud; Naher, Nahitun; Hossain, Tarek; Rawal, Lal Bahadur

2017-01-01

The private retail drug shops market in Bangladesh is largely unregulated and unaccountable, giving rise to irrational use of drugs and high Out-of-pocket expenditure on health. These shops are served by salespersons with meagre or no formal training in dispensing. This facility-based cross-sectional study was undertaken to investigate how the drug shops currently operate vis-a-vis the regulatory regime including dispensing practices of the salespersons, for identifying key action points to develop an accredited model for Bangladesh. About 90 rural and 21 urban retail drug shops from seven divisions were included in the survey. The salespersons were interviewed for relevant information, supplemented by qualitative data on perceptions of the catchment community as well as structured observation of client-provider interactions from a sub-sample. In 76% of the shops, the owner and the salesperson was the same person, and >90% of these were located within 30 min walking distance from a public sector health facility. The licensing process was perceived to be a cumbersome, lengthy, and costly process. Shop visit by drug inspectors were brief, wasn't structured, and not problem solving. Only 9% shops maintained a stock register and 10% a drug sales record. Overall, 65% clients visited drug shops without a prescription. Forty-nine percent of the salespersons had no formal training in dispensing and learned the trade through apprenticeship with fellow drug retailers (42%), relatives (18%), and village doctors (16%) etc. The catchment population of the drug shops mostly did not bother about dispensing training, drug shop licensing and buying drugs without prescription. Observed client-dispenser interactions were found to concentrate mainly on financial transaction, unless, the client pro-actively sought advice regarding the use of the drug. Majority of the drug shops studied are run by salespersons who have informal 'training' through apprenticeship. Visiting drug shops without a prescription, and dispensing without counseling unless pro-actively sought by the client, was very common. The existing process is discouraging for the shop owners to seek license, and the shop inspection visits are irregular, unstructured and punitive. These facts should be considered while designing an accredited model of drug shop for Bangladesh.

Biophysical interactions with model lipid membranes: applications in drug discovery and drug delivery

PubMed Central

Peetla, Chiranjeevi; Stine, Andrew; Labhasetwar, Vinod

2009-01-01

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

Molecular property diagnostic suite (MPDS): Development of disease-specific open source web portals for drug discovery.

PubMed

Nagamani, S; Gaur, A S; Tanneeru, K; Muneeswaran, G; Madugula, S S; Consortium, Mpds; Druzhilovskiy, D; Poroikov, V V; Sastry, G N

2017-11-01

Molecular property diagnostic suite (MPDS) is a Galaxy-based open source drug discovery and development platform. MPDS web portals are designed for several diseases, such as tuberculosis, diabetes mellitus, and other metabolic disorders, specifically aimed to evaluate and estimate the drug-likeness of a given molecule. MPDS consists of three modules, namely data libraries, data processing, and data analysis tools which are configured and interconnected to assist drug discovery for specific diseases. The data library module encompasses vast information on chemical space, wherein the MPDS compound library comprises 110.31 million unique molecules generated from public domain databases. Every molecule is assigned with a unique ID and card, which provides complete information for the molecule. Some of the modules in the MPDS are specific to the diseases, while others are non-specific. Importantly, a suitably altered protocol can be effectively generated for another disease-specific MPDS web portal by modifying some of the modules. Thus, the MPDS suite of web portals shows great promise to emerge as disease-specific portals of great value, integrating chemoinformatics, bioinformatics, molecular modelling, and structure- and analogue-based drug discovery approaches.

Interaction of ABC multidrug transporters with anticancer protein kinase inhibitors: substrates and/or inhibitors?

PubMed

Hegedus, Csilla; Ozvegy-Laczka, Csilla; Szakács, Gergely; Sarkadi, Balázs

2009-05-01

Protein kinase inhibitors (PKI) are becoming key agents in modern cancer chemotherapy, and combination of PKIs with classical chemotherapeutic drugs may help to overcome currently untreatable metastatic cancers. Since chemotherapy resistance is a recurrent problem, mechanisms of resistance should be clarified in order to help further drug development. Here we suggest that in addition to PKI resistance based on altered target structures, the active removal of these therapeutic agents by the MDR-ABC transporters should also be considered as a major cause of clinical resistance. We discuss the occurring systemic and cellular mechanisms, which may hamper PKI efficiency, and document the role of selected MDR-ABC transporters in these phenomena through their interactions with these anticancer agents. Moreover, we suggest that PKI interactions with ABC transporters may modulate overall drug metabolism, including the fate of diverse, chemically or target-wise unrelated drugs. These effects are based on multiple forms of MDR-ABC transporter interaction with PKIs, as these compounds may be both substrates and/or inhibitors of an ABC transporter. We propose that these interactions should be carefully considered in clinical application, and a combined MDR-ABC transporter and PKI effect may bring a major advantage in future drug development.

Organometallic compounds in the discovery of new agents against kinetoplastid-caused diseases.

PubMed

Ravera, Mauro; Moreno-Viguri, Elsa; Paucar, Rocio; Pérez-Silanes, Silvia; Gabano, Elisabetta

2018-06-01

The development of safe and affordable antiparasitic agents effective against neglected tropical diseases is a big challenge of the drug discovery. The drugs currently employed have limitations such as poor efficacy, drug resistance or side effects. Thus, the search for new promising drugs is more and more crucial. Metal complexes and, in particular, organometallic compounds may expand the list of the drug candidates due to the peculiar attributes that the presence of the metal core add to the organic fragment (e.g., redox and structural features, ability to interact with DNA or protein targets, etc.). To date, most organometallic compounds tested as anti-neglected tropical diseases are based on similarities or activity of the organic ligands against other diseases or parasites and/or consist in modification of existing drugs combining the features of the metal moiety and the organic ligands. This review focuses on recent studies (2012-2017) on organometallic compounds in treating kinetoplastid-caused diseases such as Human African trypanosomiasis, Chagas disease and leishmaniasis. This field of research, however, still lacks exhaustive studies to identify of parasitic targets and quantitative structure-activity relationships for a rational drug design. Copyright © 2018. Published by Elsevier Masson SAS.

Ethnobotany and Medicinal Plant Biotechnology: From Tradition to Modern Aspects of Drug Development.

PubMed

Kayser, Oliver

2018-05-24

Secondary natural products from plants are important drug leads for the development of new drug candidates for rational clinical therapy and exhibit a variety of biological activities in experimental pharmacology and serve as structural template in medicinal chemistry. The exploration of plants and discovery of natural compounds based on ethnopharmacology in combination with high sophisticated analytics is still today an important drug discovery to characterize and validate potential leads. Due to structural complexity, low abundance in biological material, and high costs in chemical synthesis, alternative ways in production like plant cell cultures, heterologous biosynthesis, and synthetic biotechnology are applied. The basis for any biotechnological process is deep knowledge in genetic regulation of pathways and protein expression with regard to todays "omics" technologies. The high number genetic techniques allowed the implementation of combinatorial biosynthesis and wide genome sequencing. Consequently, genetics allowed functional expression of biosynthetic cascades from plants and to reconstitute low-performing pathways in more productive heterologous microorganisms. Thus, de novo biosynthesis in heterologous hosts requires fundamental understanding of pathway reconstruction and multitude of genes in a foreign organism. Here, actual concepts and strategies are discussed for pathway reconstruction and genome sequencing techniques cloning tools to bridge the gap between ethnopharmaceutical drug discovery to industrial biotechnology. Georg Thieme Verlag KG Stuttgart · New York.

Development of a Soluplus budesonide freeze-dried powder for nasal drug delivery.

PubMed

Pozzoli, Michele; Traini, Daniela; Young, Paul M; Sukkar, Maria B; Sonvico, Fabio

2017-09-01

The aim of this work was to develop an amorphous solid dispersions/solutions (ASD) of a poorly soluble drug, budesonide (BUD) with a novel polymer Soluplus ® (BASF, Germany) using a freeze-drying technique, in order to improve dissolution and absorption through the nasal route. The small volume of fluid present in the nasal cavity limits the absorption of a poorly soluble drug. Budesonide is a corticosteroid, practically insoluble and normally administered as a suspension-based nasal spray. The formulation was prepared through freeze-drying of polymer-drug solution. The formulation was assessed for its physicochemical (specific surface area, calorimetric analysis and X-ray powder diffraction), release properties and aerodynamic properties as well as transport in vitro using RPMI 2650 nasal cells, in order to elucidate the efficacy of the Soluplus-BUD formulation. The freeze-dried Soluplus-BUD formulation (LYO) showed a porous structure with a specific surface area of 1.4334 ± 0.0178 m 2 /g. The calorimetric analysis confirmed an interaction between BUD and Soluplus and X-ray powder diffraction the amorphous status of the drug. The freeze-dried formulation (LYO) showed faster release compared to both water-based suspension and dry powder commercial products. Furthermore, a LYO formulation, bulked with calcium carbonate (LYO-Ca), showed suitable aerodynamic characteristics for nasal drug delivery. The permeation across RPMI 2650 nasal cell model was higher compared to a commercial water-based BUD suspension. Soluplus has been shown to be a promising polymer for the formulation of BUD amorphous solid suspension/solution. This opens up opportunities to develop new formulations of poorly soluble drug for nasal delivery.

Implications for Metabolite Quantification by Mass Spectrometry in the Absence of Authentic Standards.

PubMed

Hatsis, Panos; Waters, Nigel J; Argikar, Upendra A

2017-05-01

Quantification of metabolites by mass spectrometry in the absence of authentic reference standards or without a radiolabel is often called "semiquantitative," which acknowledges that mass spectrometric responses are not truly quantitative. For many researchers, it is tempting to pursue this practice of semiquantification in early drug discovery and even preclinical development, when radiolabeled absorption, distribution, metabolism, and excretion studies are being deferred to later stages of drug development. The caveats of quantifying metabolites based on parent drug response are explored in this investigation. A set of 71 clinically relevant drugs/metabolites encompassing common biotransformation pathways was subjected to flow injection analysis coupled with electrospray ionization (ESI) mass spectrometry. The results revealed a large variation in ESI response even for structurally similar parent drug/metabolite pairs. The ESI response of each metabolite was normalized to that of the parent drug to generate an ESI relative response factor. Overall, relative response factors ranged from 0.014 (>70-fold lower response than parent) to 8.6 (8.6-fold higher response than parent). Various two-dimensional molecular descriptors were calculated that describe physicochemical, topological, and structural properties for each drug/metabolite. The molecular descriptors, along with the ESI response factors, were used in univariate analyses as well as a principal components analysis to ascertain which molecular descriptors best account for the observed discrepancies in drug/metabolite ESI response. This investigation has shown that the practice of using parent drug response to quantify metabolites should be used with caution. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

Studying illicit drug trafficking on Darknet markets: Structure and organisation from a Canadian perspective.

PubMed

Broséus, J; Rhumorbarbe, D; Mireault, C; Ouellette, V; Crispino, F; Décary-Hétu, D

2016-07-01

Cryptomarkets are online marketplaces that are part of the Dark Web and mainly devoted to the sale of illicit drugs. They combine tools to ensure anonymity of participants with the delivery of products by mail to enable the development of illicit drug trafficking. Using data collected on eight cryptomarkets, this study provides an overview of the Canadian illicit drug market. It seeks to inform about the most prevalent illicit drugs vendors offer for sale and preferred destination countries. Moreover, the research gives an insight into the structure and organisation of distribution networks existing online. In particular, we provide information about how vendors are diversifying and replicating across marketplaces. We inform on the number of listings each vendor manages, the number of cryptomarkets they are active on and the products they offer. This research demonstrates the importance of online marketplaces in the context of illicit drug trafficking. It shows how the analysis of data available online may elicit knowledge on criminal activities. Such knowledge is mandatory to design efficient policy for monitoring or repressive purposes against anonymous marketplaces. Nevertheless, trafficking on Dark Net markets is difficult to analyse based only on digital data. A more holistic approach for investigating this crime problem should be developed. This should rely on a combined use and interpretation of digital and physical data within a single collaborative intelligence model. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

PubMed Central

Metri, Rahul; Hariharaputran, Sridhar; Ramakrishnan, Gayatri; Anand, Praveen; Raghavender, Upadhyayula S.; Ochoa-Montaño, Bernardo; Higueruelo, Alicia P.; Sowdhamini, Ramanathan; Chandra, Nagasuma R.; Blundell, Tom L.; Srinivasan, Narayanaswamy

2015-01-01

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding. Database URL: http://proline.biochem.iisc.ernet.in/sincre PMID:26130660

Response surface methodology for the determination of the design space of enantiomeric separations on cinchona-based zwitterionic chiral stationary phases by high performance liquid chromatography.

PubMed

Hanafi, Rasha Sayed; Lämmerhofer, Michael

2018-01-26

Quality-by-Design approach for enantioselective HPLC method development surpasses Quality-by-Testing in offering the optimal separation conditions with the least number of experiments and in its ability to describe the method's Design Space visually which helps to determine enantiorecognition to a significant extent. Although some schemes exist for enantiomeric separations on Cinchona-based zwitterionic stationary phases, the exact design space and the weights by which each of the chromatographic parameters influences the separation have not yet been statistically studied. In the current work, a screening design followed by a Response Surface Methodology optimization design were adopted for enantioseparation optimization of 3 model drugs namely the acidic Fmoc leucine, the amphoteric tryptophan and the basic salbutamol. The screening design proved that the acid/base additives are of utmost importance for the 3 chiral drugs, and that among 3 different pairs of acids and bases, acetic acid and diethylamine is the couple able to provide acceptable resolution at variable conditions. Visualization of the response surface of the retention factor, separation factor and resolution helped describe accurately the magnitude by which each chromatographic factor (% MeOH, concentration and ratio of acid base modifiers) affects the separation while interacting with other parameters. The global optima compromising highest enantioresolution with the least run time for the 3 chiral model drugs varied extremely, where it was best to set low % methanol with equal ratio of acid-base modifiers for the acidic drug, very high % methanol and 10-fold higher concentration of the acid for the amphoteric drug while 20 folds of the base modifier with moderate %methanol were needed for the basic drug. Considering the selected drugs as models for many series of structurally related compounds, the design space defined and the optimum conditions computed are the key for method development on cinchona-based chiral stationary phases. Copyright © 2017 Elsevier B.V. All rights reserved.

In Silico Chemogenomics Drug Repositioning Strategies for Neglected Tropical Diseases.

PubMed

Andrade, Carolina Horta; Neves, Bruno Junior; Melo-Filho, Cleber Camilo; Rodrigues, Juliana; Silva, Diego Cabral; Braga, Rodolpho Campos; Cravo, Pedro Vitor Lemos

2018-03-08

Only ~1% of all drug candidates against Neglected Tropical Diseases (NTDs) have reached clinical trials in the last decades, underscoring the need for new, safe and effective treatments. In such context, drug repositioning, which allows finding novel indications for approved drugs whose pharmacokinetic and safety profiles are already known, is emerging as a promising strategy for tackling NTDs. Chemogenomics is a direct descendent of the typical drug discovery process that involves the systematic screening of chemical compounds against drug targets in high-throughput screening (HTS) efforts, for the identification of lead compounds. However, different to the one-drug-one-target paradigm, chemogenomics attempts to identify all potential ligands for all possible targets and diseases. In this review, we summarize current methodological development efforts in drug repositioning that use state-of-the-art computational ligand- and structure-based chemogenomics approaches. Furthermore, we highlighted the recent progress in computational drug repositioning for some NTDs, based on curation and modeling of genomic, biological, and chemical data. Additionally, we also present in-house and other successful examples and suggest possible solutions to existing pitfalls. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Structures of Cryptococcus neoformans Protein Farnesyltransferase Reveal Strategies for Developing Inhibitors That Target Fungal Pathogens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hast, Michael A.; Nichols, Connie B.; Armstrong, Stephanie M.

Cryptococcus neoformans is a fungal pathogen that causes life-threatening infections in immunocompromised individuals, including AIDS patients and transplant recipients. Few antifungals can treat C. neoformans infections, and drug resistance is increasing. Protein farnesyltransferase (FTase) catalyzes post-translational lipidation of key signal transduction proteins and is essential in C. neoformans. We present a multidisciplinary study validating C. neoformans FTase (CnFTase) as a drug target, showing that several anticancer FTase inhibitors with disparate scaffolds can inhibit C. neoformans and suggesting structure-based strategies for further optimization of these leads. Structural studies are an essential element for species-specific inhibitor development strategies by revealing similarities andmore » differences between pathogen and host orthologs that can be exploited. We, therefore, present eight crystal structures of CnFTase that define the enzymatic reaction cycle, basis of ligand selection, and structurally divergent regions of the active site. Crystal structures of clinically important anticancer FTase inhibitors in complex with CnFTase reveal opportunities for optimization of selectivity for the fungal enzyme by modifying functional groups that interact with structurally diverse regions. A substrate-induced conformational change in CnFTase is observed as part of the reaction cycle, a feature that is mechanistically distinct from human FTase. Our combined structural and functional studies provide a framework for developing FTase inhibitors to treat invasive fungal infections.« less

Structural insights into substrate and inhibitor binding sites in human indoleamine 2,3-dioxygenase 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis-Ballester, Ariel; Pham, Khoa N.; Batabyal, Dipanwita

Human indoleamine 2,3-dioxygenase 1 (hIDO1) is an attractive cancer immunotherapeutic target owing to its role in promoting tumoral immune escape. However, drug development has been hindered by limited structural information. Here, we report the crystal structures of hIDO1 in complex with its substrate, Trp, an inhibitor, epacadostat, and/or an effector, indole ethanol (IDE). The data reveal structural features of the active site (Sa) critical for substrate activation; in addition, they disclose a new inhibitor-binding mode and a distinct small molecule binding site (Si). Structure-guided mutation of a critical residue, F270, to glycine perturbs the Si site, allowing structural determination ofmore » an inhibitory complex, where both the Sa and Si sites are occupied by Trp. The Si site offers a novel target site for allosteric inhibitors and a molecular explanation for the previously baffling substrate-inhibition behavior of the enzyme. Taken together, the data open exciting new avenues for structure-based drug design.« less

Essential proteins and possible therapeutic targets of Wolbachia endosymbiont and development of FiloBase-a comprehensive drug target database for Lymphatic filariasis

NASA Astrophysics Data System (ADS)

Sharma, Om Prakash; Kumar, Muthuvel Suresh

2016-01-01

Lymphatic filariasis (Lf) is one of the oldest and most debilitating tropical diseases. Millions of people are suffering from this prevalent disease. It is estimated to infect over 120 million people in at least 80 nations of the world through the tropical and subtropical regions. More than one billion people are in danger of getting affected with this life-threatening disease. Several studies were suggested its emerging limitations and resistance towards the available drugs and therapeutic targets for Lf. Therefore, better medicine and drug targets are in demand. We took an initiative to identify the essential proteins of Wolbachia endosymbiont of Brugia malayi, which are indispensable for their survival and non-homologous to human host proteins. In this current study, we have used proteome subtractive approach to screen the possible therapeutic targets for wBm. In addition, numerous literatures were mined in the hunt for potential drug targets, drugs, epitopes, crystal structures, and expressed sequence tag (EST) sequences for filarial causing nematodes. Data obtained from our study were presented in a user friendly database named FiloBase. We hope that information stored in this database may be used for further research and drug development process against filariasis. URL: http://filobase.bicpu.edu.in.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Molecular Design, Structures, and Activity of Antimicrobial Peptide-Mimetic Polymers

PubMed Central

Takahashi, Haruko; Palermo, Edmund F.; Yasuhara, Kazuma; Caputo, Gregory A.

2014-01-01

There is an urgent need for new antibiotics which are effective against drug-resistant bacteria without contributing to resistance development. We have designed and developed antimicrobial copolymers with cationic amphiphilic structures based on the mimicry of naturally occurring antimicrobial peptides. These copolymers exhibit potent antimicrobial activity against a broad spectrum of bacteria including methicillin-resistant Staphylococcus aureus with no adverse hemolytic activity. Notably, these polymers also did not result in any measurable resistance development in E. coli. The peptide-mimetic design principle offers significant flexibility and diversity in the creation of new antimicrobial materials and their potential biomedical applications. PMID:23832766

Development of new materials and structures based on managed physical-chemical factors of local interaction

NASA Astrophysics Data System (ADS)

Urakov, A. L.

2016-04-01

The paper states that assigning certain physical and chemical characteristics to pills and medical drugs solutions can substitute for the development of new drugs (which is essentially equivalent to the creation of new medicines). It is established that the purposeful change of physical and chemical characteristics of the standard ("old") materials (in other words, the known substances) is fundamental for the production of solid and liquid medicines, which allows us to get "new" structures and materials. The paper shows that assigning new physical and chemical properties to "old" materials and their further usage for the production of tablets and solutions from the "old" and well-known medicines can turn even very "old" medicine into very "novel" (moreover, even very fashionable) one with unprecedented (fantastic) pharmacological activity and new mechanisms of action.

RNA-dependent RNA polymerase: Addressing Zika outbreak by a phylogeny-based drug target study.

PubMed

Stephen, Preyesh; Lin, Sheng-Xiang

2018-01-01

Since the first major outbreak of Zika virus (ZIKV) in 2007, ZIKV is spreading explosively through South and Central America, and recent reports in highly populated developing countries alarm the possibility of a more catastrophic outbreak. ZIKV infection in pregnant women leads to embryonic microcephaly and Guillain-Barré syndrome in adults. At present, there is limited understanding of the infectious mechanism, and no approved therapy has been reported. Despite the withdrawal of public health emergency, the WHO still considers the ZIKV as a highly significant and long-term public health challenge that the situation has to be addressed rapidly. Non-structural protein 5 is essential for capping and replication of viral RNA and comprises a methyltransferase and RNA-dependent RNA polymerase (RdRp) domain. We used molecular modeling to obtain the structure of ZIKV RdRp, and by molecular docking and phylogeny analysis, we here demonstrate the potential sites for drug screening. Two metal binding sites and an NS3-interacting region in ZIKV RdRp are demonstrated as potential drug screening sites. The docked structures reveal a remarkable degree of conservation at the substrate binding site and the potential drug screening sites. A phylogeny-based approach is provided for an emergency preparedness, where similar class of ligands could target phylogenetically related proteins. © 2017 John Wiley & Sons A/S.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

PubMed Central

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

A portfolio-based approach to optimize proof-of-concept clinical trials.

PubMed

Mallinckrodt, Craig; Molenberghs, Geert; Persinger, Charles; Ruberg, Stephen; Sashegyi, Andreas; Lindborg, Stacy

2012-01-01

Improving proof-of-concept (PoC) studies is a primary lever for improving drug development. Since drug development is often done by institutions that work on multiple drugs simultaneously, the present work focused on optimum choices for rates of false positive (α) and false negative (β) results across a portfolio of PoC studies. Simple examples and a newly derived equation provided conceptual understanding of basic principles regarding optimum choices of α and β in PoC trials. In examples that incorporated realistic development costs and constraints, the levels of α and β that maximized the number of approved drugs and portfolio value varied by scenario. Optimum choices were sensitive to the probability the drug was effective and to the proportion of total investment cost prior to establishing PoC. Results of the present investigation agree with previous research in that it is important to assess optimum levels of α and β. However, the present work also highlighted the need to consider cost structure using realistic input parameters relevant to the question of interest.

Development of Platinum(iv) Complexes as Anticancer Prodrugs: the Story so Far

NASA Astrophysics Data System (ADS)

Wong, Daniel Yuan Qiang; Ang, Wee Han

2012-06-01

The serendipitous discovery of the antitumor properties of cisplatin by Barnett Rosenberg some forty years ago brought about a paradigm shift in the field of medicinal chemistry and challenged conventional thinking regarding the role of potentially toxic heavy metals in drugs. Platinum(II)-based anticancer drugs have since become some of the most effective and widely-used drugs in a clinician's arsenal and have saved countless lives. However, they are limited by high toxicity, severe side-effects and the incidence of drug resistance. In recent years, attention has shifted to stable platinum(IV) complexes as anticancer prodrugs. By exploiting the unique chemical and structural attributes of their scaffolds, these platinum(IV) prodrugs offer new strategies of targeting and killing cancer cells. This review summarizes the development of anticancer platinum(IV) prodrugs to date and some of the exciting strategies that utilise the platinum(IV) construct as targeted chemotherapeutic agents against cancer.

Extreme Entropy-Enthalpy Compensation in a Drug Resistant Variant of HIV-1 Protease

PubMed Central

King, Nancy M.; Prabu-Jeyabalan, Moses; Bandaranayake, Rajintha M.; Nalam, Madhavi N. L.; Nalivaika, Ellen A.; Özen, Ayşegül; Haliloglu, Türkan; Yılmaz, Neşe Kurt; Schiffer, Celia A.

2012-01-01

The development of HIV-1 protease inhibitors has been the historic paradigm of rational structure-based drug design, where structural and thermodynamic analyses have assisted in the discovery of novel inhibitors. While the total enthalpy and entropy change upon binding determine the affinity, often the thermodynamics are considered in terms of inhibitor properties only. In the current study, profound changes are observed in the binding thermodynamics of a drug resistant variant compared to wild-type HIV-1 protease, irrespective of the inhibitor bound. This variant (Flap+) has a combination of flap and active site mutations and exhibits extremely large entropy-enthalpy compensation compared to wild-type protease, 5–15 kcal/mol, while losing only 1–3 kcal/mol in total binding free energy for any of six FDA approved inhibitors. Although entropy-enthalpy compensation has been previously observed for a variety of systems, never have changes of this magnitude been reported. The co-crystal structures of Flap+ protease with four of the inhibitors were determined and compared with complexes of both the wildtype protease and another drug resistant variant that does not exhibit this energetic compensation. Structural changes conserved across the Flap+ complexes, which are more pronounced for the flaps covering the active site, likely contribute to the thermodynamic compensation. The finding that drug resistant mutations can profoundly modulate the relative thermodynamic properties of a therapeutic target independent of the inhibitor presents a new challenge for rational drug design. PMID:22712830

Differentiating low-molecular-weight heparins based on chemical, biological, and pharmacologic properties: implications for the development of generic versions of low-molecular-weight heparins.

PubMed

Jeske, Walter P; Walenga, Jeanine M; Hoppensteadt, Debra A; Vandenberg, Curtis; Brubaker, Aleah; Adiguzel, Cafer; Bakhos, Mamdouh; Fareed, Jawed

2008-02-01

Low-molecular-weight heparins (LMWHs) are polypharmacologic drugs used to treat thrombotic and cardiovascular disorders. These drugs are manufactured using different chemical and enzymatic methods, resulting in products with distinct chemical and pharmacologic profiles. Generic LMWHs have been introduced in Asia and South America, and several generic suppliers are seeking regulatory approval in the United States and the European Union. For simple small-molecule drugs, generic drugs have the same chemical structure, potency, and bioavailability as the innovator drug. Applying this definition to complex biological products such as the LMWHs has proved difficult. One major issue is defining appropriate criteria to demonstrate bioequivalence; pharmacopoeial specifications alone appear to be inadequate. Whereas available generic versions of LMWHs exhibit similar molecular and pharmacopoeial profiles, marked differences in their biological and pharmacologic behavior have been noted. Preliminary studies have demonstrated differences in terms of anti-Xa activity and tissue factor pathway inhibitor release after subcutaneous administration, as well as antiplatelet and profibrinolytic effects. The current data emphasize the need to consider multiple functional parameters when defining bioequivalence of biologic drugs with complex structures and activities and also underscore the importance of further pharmacologic studies involving animal models and human clinical trials. The U.S. Food and Drug Administration and the European Medicine Evaluation Agency are currently developing guidelines for the acceptance of biosimilar agents including LMWHs. Until such guidelines are complete, generic interchange may not be feasible.

Molecular modeling on streptolysin-O of multidrug resistant Streptococcus pyogenes and computer aided screening and in vitro assay for novel herbal inhibitors.

PubMed

Skariyachan, Sinosh; Narayan, Naik Sowmyalaxmi; Aggimath, Tejaswini S; Nagaraj, Sushmitha; Reddy, Monika S; Narayanappa, Rajeswari

2014-03-01

Streptococcus pyogenes is a notorious pathogenic bacterium which causes various human diseases ranging from localized infections to life threatening invasive diseases. Streptolysin-O (SLO), pore-forming thiol-activated cytolysin, is the major virulent factor for streptococcal infections. Present therapies against streptococcal infections are limited as most of the strains have developed multi-drug resistance to present generation of drugs. Hence, there is a need for alternative therapeutic substances. Structure based virtual screening is a novel platform to select lead molecules with better pharmacokinetic properties. The 3D structure of SLO (not available in native form), essential for such studies, was computationally generated and this homology model was used as probable drug target. Based on literature survey, several phytoligands from 25 medicinal plants were selected. Out of these, leads from 11 plants showed better pharmacokinetic properties. The best lead molecules were screened based on computer aided drug likeness and pharmacokinetic predictions. The inhibitory properties of selected herbal leads against SLO were studied by molecular docking. An in vitro assay was further carried out and variations observed were found to be significant (p<0.05). Antibiotic sensitivity testing was also performed with the clinical strain of Streptococcus pyogenes with conventional drugs. The clinical strain showed multi-drug resistance to conventional drugs. Our study revealed that numerous phytoligands have better inhibitory properties towards the toxin. We noticed that incorporation of selected herbal extracts in blood agar medium showed significant reduction in hemolysis (MIC 300μl/plate), indicating inhibition of SLO. Furthermore, the butanol extracts of selected herbal preparation based on computer aided screening showed significant inhibitory properties at 250 mcg/disc concentration. We also noticed that selected herbal formulations have better antimicrobial properties at MIC range of 300- 400μl. Hence, our study suggests that these herbal extracts have better inhibitory properties against the toxin as well as drug resistant Streptococcus pyogenes.

Engineering dextran-based scaffolds for drug delivery and tissue repair

PubMed Central

Sun, Guoming; Mao, Jeremy J

2015-01-01

Owing to its chemically reactive hydroxyl groups, dextran can be modified with different functional groups to form spherical, tubular and 3D network structures. The development of novel functional scaffolds for efficient controlled release and tissue regeneration has been a major research interest, and offers promising therapeutics for many diseases. Dextran-based scaffolds are naturally biodegradable and can serve as bioactive carriers for many protein biomolecules. The reconstruction of the in vitro microenvironment with proper signaling cues for large-scale tissue regenerative scaffolds has yet to be fully developed, and remains a significant challenge in regenerative medicine. This paper will describe recent advances in dextran-based polymers and scaffolds for controlled release and tissue engineering. Special attention is given to the development of dextran-based hydrogels that are precisely manipulated with desired structural properties and encapsulated with defined angiogenic growth factors for therapeutic neovascularization, as well as their potential for wound repair. PMID:23210716

Structure-based drug design: docking and scoring.

PubMed

Kroemer, Romano T

2007-08-01

This review gives an introduction into ligand - receptor docking and illustrates the basic underlying concepts. An overview of different approaches and algorithms is provided. Although the application of docking and scoring has led to some remarkable successes, there are still some major challenges ahead, which are outlined here as well. Approaches to address some of these challenges and the latest developments in the area are presented. Some aspects of the assessment of docking program performance are discussed. A number of successful applications of structure-based virtual screening are described.

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

PubMed

Bender, Andreas; Scheiber, Josef; Glick, Meir; Davies, John W; Azzaoui, Kamal; Hamon, Jacques; Urban, Laszlo; Whitebread, Steven; Jenkins, Jeremy L

2007-06-01

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.

Uridine monophosphate kinase as potential target for tuberculosis: from target to lead identification.

PubMed

Arvind, Akanksha; Jain, Vaibhav; Saravanan, Parameswaran; Mohan, C Gopi

2013-12-01

Mycobacterium tuberculosis (Mtb) is a causative agent of tuberculosis (TB) disease, which has affected approximately 2 billion people worldwide. Due to the emergence of resistance towards the existing drugs, discovery of new anti-TB drugs is an important global healthcare challenge. To address this problem, there is an urgent need to identify new drug targets in Mtb. In the present study, the subtractive genomics approach has been employed for the identification of new drug targets against TB. Screening the Mtb proteome using the Database of Essential Genes (DEG) and human proteome resulted in the identification of 60 key proteins which have no eukaryotic counterparts. Critical analysis of these proteins using Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database revealed uridine monophosphate kinase (UMPK) enzyme as a potential drug target for developing novel anti-TB drugs. Homology model of Mtb-UMPK was constructed for the first time on the basis of the crystal structure of E. coli-UMPK, in order to understand its structure-function relationships, and which would in turn facilitate to perform structure-based inhibitor design. Furthermore, the structural similarity search was carried out using physiological inhibitor UTP of Mtb-UMPK to virtually screen ZINC database. Retrieved hits were further screened by implementing several filters like ADME and toxicity followed by molecular docking. Finally, on the basis of the Glide docking score and the mode of binding, 6 putative leads were identified as inhibitors of this enzyme which can potentially emerge as future drugs for the treatment of TB.

Drugs & the Brain: Case-based Instruction for an Undergraduate Neuropharmacology Course.

PubMed

Nagel, Anastasia; Nicholas, Andrea

2017-01-01

In order to transform a traditional large non-majors general education (GE) neurobiology lecture (Drugs & the Brain) into an active learning course, we developed a series of directed mini-cases targeting major drug classes. Humorous and captivating case-based situations were used to better engage and motivate students to solve problems related to neuropharmacology and physiology. Here we provide directed cases, questions and learning outcomes for our opiates mini-cases. In addition, we describe how case studies were incorporated into our course and assessed using peer review and online quizzing. An in-depth analysis of the overall course transformation on student exam performance, opinions and instructor evaluations can be found in the JUNE article Don't Believe the Gripe! Increasing Course Structure in a Large Non-majors Neuroscience Course.

Learning the Structure of Biomedical Relationships from Unstructured Text

PubMed Central

Percha, Bethany; Altman, Russ B.

2015-01-01

The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured text of over 23 million articles. The creation of structured resources that catalog the relationships between drugs and genes would accelerate the translation of basic molecular knowledge into discoveries of genomic biomarkers for drug response and prediction of unexpected drug-drug interactions. Extracting these relationships from natural language sentences on such a large scale, however, requires text mining algorithms that can recognize when different-looking statements are expressing similar ideas. Here we describe a novel algorithm, Ensemble Biclustering for Classification (EBC), that learns the structure of biomedical relationships automatically from text, overcoming differences in word choice and sentence structure. We validate EBC's performance against manually-curated sets of (1) pharmacogenomic relationships from PharmGKB and (2) drug-target relationships from DrugBank, and use it to discover new drug-gene relationships for both knowledge bases. We then apply EBC to map the complete universe of drug-gene relationships based on their descriptions in Medline, revealing unexpected structure that challenges current notions about how these relationships are expressed in text. For instance, we learn that newer experimental findings are described in consistently different ways than established knowledge, and that seemingly pure classes of relationships can exhibit interesting chimeric structure. The EBC algorithm is flexible and adaptable to a wide range of problems in biomedical text mining. PMID:26219079

Structural interpretation of P2X receptor mutagenesis studies on drug action

PubMed Central

Evans, Richard J

2010-01-01

P2X receptors for ATP are ligand gated cation channels that form from the trimeric assembly of subunits with two transmembrane segments, a large extracellular ligand binding loop, and intracellular amino and carboxy termini. The receptors are expressed throughout the body, involved in functions ranging from blood clotting to inflammation, and may provide important targets for novel therapeutics. Mutagenesis based studies have been used to develop an understanding of the molecular basis of their pharmacology with the aim of developing models of the ligand binding site. A crystal structure for the zebra fish P2X4 receptor in the closed agonist unbound state has been published recently, which provides a major advance in our understanding of the receptors. This review gives an overview of mutagenesis studies that have led to the development of a model of the ATP binding site, as well as identifying residues contributing to allosteric regulation and antagonism. These studies are discussed with reference to the crystal to provide a structural interpretation of the molecular basis of drug action. PMID:20977449

Geographic approaches to quantifying the risk environment: a focus on syringe exchange program site access and drug-related law enforcement activities

PubMed Central

Cooper, Hannah LF; Bossak, Brian; Tempalski, Barbara; Des Jarlais, Don C.; Friedman, Samuel R.

2009-01-01

The concept of the “risk environment” – defined as the “space … [where] factors exogenous to the individual interact to increase the chances of HIV transmission” – draws together the disciplines of public health and geography. Researchers have increasingly turned to geographic methods to quantify dimensions of the risk environment that are both structural and spatial (e.g., local poverty rates). The scientific power of the intersection between public health and geography, however, has yet to be fully mined. In particular, research on the risk environment has rarely applied geographic methods to create neighbourhood-based measures of syringe exchange programs (SEPs) or of drug-related law enforcement activities, despite the fact that these interventions are widely conceptualized as structural and spatial in nature and are two of the most well-established dimensions of the risk environment. To strengthen research on the risk environment, this paper presents a way of using geographic methods to create neighbourhood-based measures of (1) access to SEP sites and (2) exposure to drug-related arrests, and then applies these methods to one setting (New York City). NYC-based results identified substantial cross-neighbourhood variation in SEP site access and in exposure to drug-related arrest rates (even within the subset of neighbourhoods nominally experiencing the same drug-related police strategy). These geographic measures – grounded as they are in conceptualizations of SEPs and drug-related law enforcement strategies – can help develop new arenas of inquiry regarding the impact of these two dimensions of the risk environment on injectors’ health, including exploring whether and how neighbourhood-level access to SEP sites and exposure to drug-related arrests shape a range of outcomes among local injectors. PMID:18963907

Application of metabonomics in a compound ranking study in early drug development revealing drug-induced excretion of choline into urine.

PubMed

Dieterle, Frank; Schlotterbeck, Götz; Ross, Alfred; Niederhauser, Urs; Senn, Hans

2006-09-01

Selecting drug candidates based on toxicity is an important step in early drug development. In this case study, it is shown how metabonomics is applied to a ranking study, in which drug candidates with equal pharmacological activities are selected based on least toxic side effects. The metabonomic analyses were carried out on an animal study that followed an established protocol for pilot toxicology/ranking studies in rats, however, not specifically modified for a metabonomic assessment. It is shown how conditions not specificially adopted for metabonomics investigations can significantly influence the metabolic profiles recorded by NMR. Furthermore, it is shown how the multivariate analysis of the NMR spectra identified an extreme excretion of an endogenous metabolite into urine induced by two out of the five drug candidates. The subsequent structure elucidation by two-dimensional NMR experiments and a subsequent validation by spiking experiments identified the metabolite as choline. The discussion of the mechanistic background for the excretion of choline, which is usually well-conserved in the body, results in two hypotheses of either a massive degradation of cell membranes or an inhibition of the choline oxidation. Although the validation of these hypotheses needs a follow-up study, the finding of a increased excretion of the important metabolite choline warrants exclusion of these two compounds as viable drug candidates from a metabonomics point of view.

Cloud Computing for Protein-Ligand Binding Site Comparison

PubMed Central

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery. PMID:23762824

Cloud computing for protein-ligand binding site comparison.

PubMed

Hung, Che-Lun; Hua, Guan-Jie

2013-01-01

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.

Designer drugs: the evolving science of drug discovery.

PubMed

Wanke, L A; DuBose, R F

1998-07-01

Drug discovery and design are fundamental to drug development. Until recently, most drugs were discovered through random screening or developed through molecular modification. New technologies are revolutionizing this phase of drug development. Rational drug design, using powerful computers and computational chemistry and employing X-ray crystallography, nuclear magnetic resonance spectroscopy, and three-dimensional quantitative structure activity relationship analysis, is creating highly specific, biologically active molecules by virtual reality modeling. Sophisticated screening technologies are eliminating all but the most active lead compounds. These new technologies promise more efficacious, safe, and cost-effective medications, while minimizing drug development time and maximizing profits.

TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer

PubMed Central

2014-01-01

Background Non-small cell lung cancer (NSCLC) remains lethal despite the development of numerous drug therapy technologies. About 85% to 90% of lung cancers are NSCLC and the 5-year survival rate is at best still below 50%. Thus, it is important to find drugable target genes for NSCLC to develop an effective therapy for NSCLC. Results Integrated analysis of publically available gene expression and promoter methylation patterns of two highly aggressive NSCLC cell lines generated by in vivo selection was performed. We selected eleven critical genes that may mediate metastasis using recently proposed principal component analysis based unsupervised feature extraction. The eleven selected genes were significantly related to cancer diagnosis. The tertiary protein structure of the selected genes was inferred by Full Automatic Modeling System, a profile-based protein structure inference software, to determine protein functions and to specify genes that could be potential drug targets. Conclusions We identified eleven potentially critical genes that may mediate NSCLC metastasis using bioinformatic analysis of publically available data sets. These genes are potential target genes for the therapy of NSCLC. Among the eleven genes, TINAGL1 and B3GALNT1 are possible candidates for drug compounds that inhibit their gene expression. PMID:25521548

Moving evidence-based drug abuse prevention programs from basic science to practice: "bridging the efficacy-effectiveness interface".

PubMed

August, Gerald J; Winters, Ken C; Realmuto, George M; Tarter, Ralph; Perry, Cheryl; Hektner, Joel M

2004-01-01

This article examines the challenges faced by developers of youth drug abuse prevention programs in transporting scientifically proven or evidence-based programs into natural community practice systems. Models for research on the transfer of prevention technology are described with specific emphasis given to the relationship between efficacy and effectiveness studies. Barriers that impede the successful integration of efficacy methods within effectiveness studies (e.g., client factors, practitioner factors, intervention structure characteristics, and environmental and organizational factors) are discussed. We present a modified model for program development and evaluation that includes a new type of research design, the hybrid efficacy-effectiveness study that addresses program transportability. The utility of the hybrid study is illustrated in the evaluation of the Early Risers "Skills for Success" prevention program.

Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming.

PubMed

Li, Yuqin; You, Guirong; Jia, Baoxiu; Si, Hongzong; Yao, Xiaojun

2014-01-01

Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R (2)) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.

HIV-1 reverse transcriptase and antiviral drug resistance. Part 2.

PubMed

Das, Kalyan; Arnold, Eddy

2013-04-01

Structures of RT and its complexes combined with biochemical and clinical data help in illuminating the molecular mechanisms of different drug-resistance mutations. The NRTI drugs that are used in combinations have different primary mutation sites. RT mutations that confer resistance to one drug can be hypersensitive to another RT drug. Structure of an RT-DNA-nevirapine complex revealed how NNRTI binding forbids RT from forming a polymerase competent complex. Collective knowledge about various mechanisms of drug resistance by RT has broader implications for understanding and targeting drug resistance in general. In Part 1, we discussed the role of RT in developing HIV-1 drug resistance, structural and functional states of RT, and the nucleoside/nucleotide analog (NRTI) and non-nucleoside (NNRTI) drugs used in treating HIV-1 infections. In this part, we discuss structural understanding of various mechanisms by which RT confers antiviral drug resistance. Copyright © 2013 Elsevier B.V. All rights reserved.

Biosimilar drugs in Mexico: position of the Mexican College of Rheumatology, 2012.

PubMed

Espinosa Morales, Rolando; Díaz Borjón, Alejandro; Barile Fabris, Leonor Adriana; Esquivel Valerio, Jorge Antonio; Medrano Ramírez, Gabriel; Arce Salinas, César Alejandro; Barreira Mercado, Eduardo Rubén; Cardiel Ríos, Mario Humberto; Díaz Jouanen, Efraín; Flores Murrieta, Francisco Javier; Fraga Mouret, Antonio; Garza Elizondo, Mario Alberto; Luján Estrada, Miguel; Muñoz Barradas, Francisco José; Talavera Piña, Juan Osvaldo; Vera Lastra, Olga Lidia

2013-01-01

Biotechnological drugs (BTDs) are complex molecules whose manufacturing process precludes the ability to identically reproduce the structure of the original product, and therefore there cannot be an absolute equivalence between the original (innovative) medication and its biosimilar counterpart. BTDs have been proven useful in the treatment of several rheumatic diseases, however their high cost has prevented their use in many patients. Several BTD patents have expired or are close to expire, triggering the development of structurally similar drugs with efficacy and safety profiles comparable to the innovative compound; however, these must be evaluated through evidence based medicine. The Mexican General Health Law contemplates the registry of these biosimilar drugs for their use in our country. This document is a forethought from members of the Mexican College of Rheumatology, pharmacologists, and epidemiologists, in accordance with Mexican health authorities regarding the necessary scientific evidence required to evaluate the efficacy and safety of biosimilar drugs before and after their arrival to the Mexican market. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Quantitative systems toxicology

PubMed Central

Bloomingdale, Peter; Housand, Conrad; Apgar, Joshua F.; Millard, Bjorn L.; Mager, Donald E.; Burke, John M.; Shah, Dhaval K.

2017-01-01

The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of evaluating the adverse effects of drugs in animals to predict human health risks. The U.S. Environmental Protection Agency recognized the need to develop innovative toxicity testing strategies and asked the National Research Council to develop a long-range vision and strategy for toxicity testing in the 21st century. The vision aims to reduce the use of animals and drug development costs through the integration of computational modeling and in vitro experimental methods that evaluates the perturbation of toxicity-related pathways. Towards this vision, collaborative quantitative systems pharmacology and toxicology modeling endeavors (QSP/QST) have been initiated amongst numerous organizations worldwide. In this article, we discuss how quantitative structure-activity relationship (QSAR), network-based, and pharmacokinetic/pharmacodynamic modeling approaches can be integrated into the framework of QST models. Additionally, we review the application of QST models to predict cardiotoxicity and hepatotoxicity of drugs throughout their development. Cell and organ specific QST models are likely to become an essential component of modern toxicity testing, and provides a solid foundation towards determining individualized therapeutic windows to improve patient safety. PMID:29308440

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

DOE PAGES

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.; ...

2017-05-02

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Small molecule inhibitors of mesotrypsin from a structure-based docking screen

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.

PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less

Structure-based drug design of RN486, a potent and selective Bruton's tyrosine kinase (BTK) inhibitor, for the treatment of rheumatoid arthritis.

PubMed

Lou, Yan; Han, Xiaochun; Kuglstatter, Andreas; Kondru, Rama K; Sweeney, Zachary K; Soth, Michael; McIntosh, Joel; Litman, Renee; Suh, Judy; Kocer, Buelent; Davis, Dana; Park, Jaehyeon; Frauchiger, Sandra; Dewdney, Nolan; Zecic, Hasim; Taygerly, Joshua P; Sarma, Keshab; Hong, Junbae; Hill, Ronald J; Gabriel, Tobias; Goldstein, David M; Owens, Timothy D

2015-01-08

Structure-based drug design was used to guide the optimization of a series of selective BTK inhibitors as potential treatments for Rheumatoid arthritis. Highlights include the introduction of a benzyl alcohol group and a fluorine substitution, each of which resulted in over 10-fold increase in activity. Concurrent optimization of drug-like properties led to compound 1 (RN486) ( J. Pharmacol. Exp. Ther. 2012 , 341 , 90 ), which was selected for advanced preclinical characterization based on its favorable properties.

Computer-Aided Drug Design Methods.

PubMed

Yu, Wenbo; MacKerell, Alexander D

2017-01-01

Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure-based drug design (SBDD) and ligand-based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

A new class of HIV-1 protease inhibitor: the crystallographic structure, inhibition and chemical synthesis of an aminimide peptide isostere.

PubMed

Rutenber, E E; McPhee, F; Kaplan, A P; Gallion, S L; Hogan, J C; Craik, C S; Stroud, R M

1996-09-01

The essential role of HIV-1 protease (HIV-1 PR) in the viral life cycle makes it an attractive target for the development of substrate-based inhibitors that may find efficacy as anti-AIDS drugs. However, resistance has arisen to potent peptidomimetic drugs necessitating the further development of novel chemical backbones for diversity based chemistry focused on probing the active site for inhibitor interactions and binding modes that evade protease resistance. AQ148 is a potent inhibitor of HIV-1 PR and represents a new class of transition state analogues incorporating an aminimide peptide isostere. A 3-D crystallographic structure of AQ148, a tetrapeptide isostere, has been determined in complex with its target HIV-1 PR to a resolution of 2.5 A and used to evaluate the specific structural determinants of AQ148 potency and to correlate structure-activity relationships within the class of related compounds. AQ148 is a competitive inhibitor of HIV-1 PR with a Ki value of 137 nM. Twenty-nine derivatives have been synthesized and chemical modifications have been made at the P1, P2, P1', and P2' sites. The atomic resolution structure of AQ148 bound to HIV-1 PR reveals both an inhibitor binding mode that closely resembles that of other peptidomimetic inhibitors and specific protein/inhibitor interactions that correlate with structure-activity relationships. The structure provides the basis for the design, synthesis and evaluation of the next generation of hydroxyethyl aminimide inhibitors. The aminimide peptide isostere is a scaffold with favorable biological properties well suited to both the combinatorial methods of peptidomimesis and the rational design of potent and specific substrate-based analogues.

An emerging platform for drug delivery: aerogel based systems.

PubMed

Ulker, Zeynep; Erkey, Can

2014-03-10

Over the past few decades, advances in "aerogel science" have provoked an increasing interest for these materials in pharmaceutical sciences for drug delivery applications. Because of their high surface areas, high porosities and open pore structures which can be tuned and controlled by manipulation of synthesis conditions, nanostructured aerogels represent a promising class of materials for delivery of various drugs as well as enzymes and proteins. Along with biocompatible inorganic aerogels and biodegradable organic aerogels, more complex systems such as surface functionalized aerogels, composite aerogels and layered aerogels have also been under development and possess huge potential. Emphasis is given to the details of the aerogel synthesis and drug loading methods as well as the influence of synthesis parameters and loading methods on the adsorption and release of the drugs. Owing to their ability to increase the bioavailability of low solubility drugs, to improve both their stability and their release kinetics, there are an increasing number of research articles concerning aerogels in different drug delivery applications. This review presents an up to date overview of the advances in all kinds of aerogel based drug delivery systems which are currently under investigation. Copyright © 2014 Elsevier B.V. All rights reserved.

Steroid Sulfatase Inhibition by Aryl Sulfamates: Clinical Progress, Mechanism and Future Prospects.

PubMed

Potter, Barry V L

2018-04-04

Steroid sulfatase is an emerging drug target for the endocrine therapy of hormone-dependent diseases, catalyzing estrogen sulfate hydrolysis to estrogen. Drug discovery, developing the core aryl O-sulfamate pharmacophore, has led to steroidal and non-steroidal drugs entering numerous clinical trials, with promising results in oncology and women's health. Steroidal estrogen sulfamate derivatives were the first irreversible active-site-directed inhibitors and one was developed clinically as an oral estradiol pro-drug and for endometriosis applications. This review summarizes work leading to the therapeutic concept of sulfatase inhibition, clinical trials executed to date and new insights into the mechanism of inhibition of steroid sulfatase. To date the non-steroidal sulfatase inhibitor Irosustat has been evaluated clinically in breast cancer, alone and in combination, in endometrial cancer and in prostate cancer. The versatile core pharmacophore both imbues attractive pharmaceutical properties and functions via three distinct mechanisms of action, as a pro-drug, an enzyme active site-modifying motif, likely through direct sulfamoyl group transfer, and as a structural component augmenting activity, for example by enhancing interactions at the colchicine binding site of tubulin. Preliminary new structural data on the Pseudomonas aeruginosa arylsulfatase enzyme suggest two possible sulfamate-based adducts with active site hydrated formylglycine as candidates for the inhibition end product via sulfamoyl group transfer, and a speculative choice is suggested. The clinical status of sulfatase inhibition is surveyed and how it might develop in the future. Also discussed are dual-targeting approaches, development of 2-substituted steroidal sulfamates and nonsteroidal derivatives as multi-targeting agents for hormone-independent tumours with other emerging directions.

Automatically Recognizing Medication and Adverse Event Information From Food and Drug Administration’s Adverse Event Reporting System Narratives

PubMed Central

Polepalli Ramesh, Balaji; Belknap, Steven M; Li, Zuofeng; Frid, Nadya; West, Dennis P

2014-01-01

Background The Food and Drug Administration’s (FDA) Adverse Event Reporting System (FAERS) is a repository of spontaneously-reported adverse drug events (ADEs) for FDA-approved prescription drugs. FAERS reports include both structured reports and unstructured narratives. The narratives often include essential information for evaluation of the severity, causality, and description of ADEs that are not present in the structured data. The timely identification of unknown toxicities of prescription drugs is an important, unsolved problem. Objective The objective of this study was to develop an annotated corpus of FAERS narratives and biomedical named entity tagger to automatically identify ADE related information in the FAERS narratives. Methods We developed an annotation guideline and annotate medication information and adverse event related entities on 122 FAERS narratives comprising approximately 23,000 word tokens. A named entity tagger using supervised machine learning approaches was built for detecting medication information and adverse event entities using various categories of features. Results The annotated corpus had an agreement of over .9 Cohen’s kappa for medication and adverse event entities. The best performing tagger achieves an overall performance of 0.73 F1 score for detection of medication, adverse event and other named entities. Conclusions In this study, we developed an annotated corpus of FAERS narratives and machine learning based models for automatically extracting medication and adverse event information from the FAERS narratives. Our study is an important step towards enriching the FAERS data for postmarketing pharmacovigilance. PMID:25600332

Smallpox Antiviral Drug

DTIC Science & Technology

2006-01-01

preparing a Continuation in Part ( CIP ) to add the new I7L cleavage assays recently developed by SIGA. Conclusions By using homology-based... developmental cycle . RNA viruses and retroviruses commonly undergo formative proteolysis in which large polyproteins are cleaved by viral encoded proteinases to...structural model of the vaccinia virus (VV) I7L proteinase was developed at Transtech Pharma. A unique chemical library of ~ 51,000 compounds was

Crystal structures of ASK1-inhibtor complexes provide a platform for structure-based drug design

PubMed Central

Singh, Onkar; Shillings, Anthony; Craggs, Peter; Wall, Ian; Rowland, Paul; Skarzynski, Tadeusz; Hobbs, Clare I; Hardwick, Phil; Tanner, Rob; Blunt, Michelle; Witty, David R; Smith, Kathrine J

2013-01-01

ASK1, a member of the MAPK Kinase Kinase family of proteins has been shown to play a key role in cancer, neurodegeneration and cardiovascular diseases and is emerging as a possible drug target. Here we describe a ‘replacement-soaking’ method that has enabled the high-throughput X-ray structure determination of ASK1/ligand complexes. Comparison of the X-ray structures of five ASK1/ligand complexes from 3 different chemotypes illustrates that the ASK1 ATP binding site is able to accommodate a range of chemical diversity and different binding modes. The replacement-soaking system is also able to tolerate some protein flexibility. This crystal system provides a robust platform for ASK1/ligand structure determination and future structure based drug design. PMID:23776076

Engineering Archeal Surrogate Systems for the Development of Protein-Protein Interaction Inhibitors against Human RAD51.

PubMed

Moschetti, Tommaso; Sharpe, Timothy; Fischer, Gerhard; Marsh, May E; Ng, Hong Kin; Morgan, Matthew; Scott, Duncan E; Blundell, Tom L; R Venkitaraman, Ashok; Skidmore, John; Abell, Chris; Hyvönen, Marko

2016-11-20

Protein-protein interactions (PPIs) are increasingly important targets for drug discovery. Efficient fragment-based drug discovery approaches to tackle PPIs are often stymied by difficulties in the production of stable, unliganded target proteins. Here, we report an approach that exploits protein engineering to "humanise" thermophilic archeal surrogate proteins as targets for small-molecule inhibitor discovery and to exemplify this approach in the development of inhibitors against the PPI between the recombinase RAD51 and tumour suppressor BRCA2. As human RAD51 has proved impossible to produce in a form that is compatible with the requirements of fragment-based drug discovery, we have developed a surrogate protein system using RadA from Pyrococcus furiosus. Using a monomerised RadA as our starting point, we have adopted two parallel and mutually instructive approaches to mimic the human enzyme: firstly by mutating RadA to increase sequence identity with RAD51 in the BRC repeat binding sites, and secondly by generating a chimeric archaeal human protein. Both approaches generate proteins that interact with a fourth BRC repeat with affinity and stoichiometry comparable to human RAD51. Stepwise humanisation has also allowed us to elucidate the determinants of RAD51 binding to BRC repeats and the contributions of key interacting residues to this interaction. These surrogate proteins have enabled the development of biochemical and biophysical assays in our ongoing fragment-based small-molecule inhibitor programme and they have allowed us to determine hundreds of liganded structures in support of our structure-guided design process, demonstrating the feasibility and advantages of using archeal surrogates to overcome difficulties in handling human proteins. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multiple e-pharmacophore modelling pooled with high-throughput virtual screening, docking and molecular dynamics simulations to discover potential inhibitors of Plasmodium falciparum lactate dehydrogenase (PfLDH).

PubMed

Saxena, Shalini; Durgam, Laxman; Guruprasad, Lalitha

2018-05-14

Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10 2 -1.3 × 10 6  nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.

Designing of phenol-based β-carbonic anhydrase1 inhibitors through QSAR, molecular docking, and MD simulation approach.

PubMed

Ahamad, Shahzaib; Hassan, Md Imtaiyaz; Dwivedi, Neeraja

2018-05-01

Tuberculosis (Tb) is an airborne infectious disease caused by Mycobacterium tuberculosis. Beta-carbonic anhydrase 1 ( β-CA1 ) has emerged as one of the potential targets for new antitubercular drug development. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulation approaches were performed on a series of natural and synthetic phenol-based β-CA1 inhibitors. The developed 3D-QSAR model ( r 2  = 0.94, q 2  = 0.86, and pred_r 2  = 0.74) indicated that the steric and electrostatic factors are important parameters to modulate the bioactivity of phenolic compounds. Based on this indication, we designed 72 new phenolic inhibitors, out of which two compounds (D25 and D50) effectively stabilized β-CA1 receptor and, thus, are potential candidates for new generation antitubercular drug discovery program.

Predicting targets of compounds against neurological diseases using cheminformatic methodology

NASA Astrophysics Data System (ADS)

Nikolic, Katarina; Mavridis, Lazaros; Bautista-Aguilera, Oscar M.; Marco-Contelles, José; Stark, Holger; do Carmo Carreiras, Maria; Rossi, Ilaria; Massarelli, Paola; Agbaba, Danica; Ramsay, Rona R.; Mitchell, John B. O.

2015-02-01

Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand ( 71/MBA-VEG8).

Structure Based Discovery of Pan Active Botulinum Neurotoxin Inhibitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vieni, Casey; McGillick, Brian; Kumaran, Desigan

Clostridium botulinum neurotoxins (BoNTs) released by the bacterium Clostridium botulinum are the most potent toxins causing the fatal disease called botulism. There are seven distinct serotypes of BoNTs (A to G) released by various strains of botulinum. They all have high sequence homology and similar three-dimensional structure. The toxicity of BoNT follows a four-step process – binding, internalization, translocation, and cleavage of its target protein, one of the three components of the SNARE complex (Soluble N-ethylmaleimde-sensitive factor attachment protein receptor) required for membrane docking and neurotransmitter release. Cleavage of one of the three proteins causes blockage of neurotransmitter release leadingmore » to flaccid paralysis. Though anyone of the above four steps could be a target for developing antidotes for botulism, the catalytic domain is the most suitable target for post exposure treatment. Of the seven serotypes BoNT/A, B, E and probably F affect humans, with BoNT/A considered to be the most potent. Development of drugs for botulism is focused on serotype specific inhibitors, but a pan-active inhibitor acting on several serotypes is preferable since it is difficult to identify the serotype before the treatment, especially since there is at least a 36-hour window before botulism can be diagnosed. Using structure-based drug discovery, we have developed three heptapeptides based on the SNARE proteins which inhibit BoNT/A, B and E equally well. Probable reasons for pan-activity of these peptides are discussed.« less

Structure Based Discovery of Pan Active Botulinum Neurotoxin Inhibitors

DOE PAGES

Vieni, Casey; McGillick, Brian; Kumaran, Desigan; ...

2018-02-14

Clostridium botulinum neurotoxins (BoNTs) released by the bacterium Clostridium botulinum are the most potent toxins causing the fatal disease called botulism. There are seven distinct serotypes of BoNTs (A to G) released by various strains of botulinum. They all have high sequence homology and similar three-dimensional structure. The toxicity of BoNT follows a four-step process – binding, internalization, translocation, and cleavage of its target protein, one of the three components of the SNARE complex (Soluble N-ethylmaleimde-sensitive factor attachment protein receptor) required for membrane docking and neurotransmitter release. Cleavage of one of the three proteins causes blockage of neurotransmitter release leadingmore » to flaccid paralysis. Though anyone of the above four steps could be a target for developing antidotes for botulism, the catalytic domain is the most suitable target for post exposure treatment. Of the seven serotypes BoNT/A, B, E and probably F affect humans, with BoNT/A considered to be the most potent. Development of drugs for botulism is focused on serotype specific inhibitors, but a pan-active inhibitor acting on several serotypes is preferable since it is difficult to identify the serotype before the treatment, especially since there is at least a 36-hour window before botulism can be diagnosed. Using structure-based drug discovery, we have developed three heptapeptides based on the SNARE proteins which inhibit BoNT/A, B and E equally well. Probable reasons for pan-activity of these peptides are discussed.« less

Molecular Docking of Enzyme Inhibitors: A Computational Tool for Structure-Based Drug Design

ERIC Educational Resources Information Center

Rudnitskaya, Aleksandra; Torok, Bela; Torok, Marianna

2010-01-01

Molecular docking is a frequently used method in structure-based rational drug design. It is used for evaluating the complex formation of small ligands with large biomolecules, predicting the strength of the bonding forces and finding the best geometrical arrangements. The major goal of this advanced undergraduate biochemistry laboratory exercise…

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

PubMed

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus

PubMed Central

Ekins, Sean; Freundlich, Joel S.; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested. PMID:25653841

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

PubMed

Randhawa, Vinay; Kumar Singh, Anil; Acharya, Vishal

2015-12-01

Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize the effectiveness of such pipelines, we first analyzed the dysregulated gene pairs between control and tumor samples and then implemented an ensemble-based feature selection approach to prioritize targets in oral squamous cell carcinoma (OSCC) for therapeutic exploration. Based on the structural information of known inhibitors of CXCR4-one of the best targets identified in this study-a feature selection was implemented for the identification of optimal structural features (molecular descriptor) based on which a classification model was generated. Furthermore, the CXCR4-centered descriptor-based classification model was finally utilized to screen a repository of plant derived small-molecules to obtain potential inhibitors. The application of our methodology may assist effective selection of the best targets which may have previously been overlooked, that in turn will lead to the development of new oral cancer medications. The small molecules identified in this study can be ideal candidates for trials as potential novel anti-oral cancer agents. Importantly, distinct steps of this whole study may provide reference for the analysis of other complex human diseases.

In vivo biocompatibility and in vitro characterization of poly-lactide-co-glycolide structures containing levetiracetam, for the treatment of epilepsy.

PubMed

Halliday, Amy J; Campbell, Toni E; Razal, Joselito M; McLean, Karen J; Nelson, Timothy S; Cook, Mark J; Wallace, Gordon G

2012-02-01

Epilepsy is a chronic neurological disorder characterized by recurrent seizures, and is highly resistant to medication with up to 40% of patients continuing to experience seizures whilst taking oral antiepileptic drugs. Recent research suggests that this may be due to abnormalities in the blood-brain barrier, which prevent the passage of therapeutic substances into the brain. We sought to develop a drug delivery material that could be implanted within the brain at the origin of the seizures to release antiepileptic drugs locally and avoid the blood brain barrier. We produced poly-lactide-co-glycolide drop-cast films and wet-spun fibers loaded with the novel antiepileptic drug Levetiracetam, and investigated their morphology, in vitro drug release characteristics, and brain biocompatibility in adult rats. The best performing structures released Levetiracetam constantly for at least 5 months in vitro, and were found to be highly brain biocompatible following month-long implantations in the motor cortex of adult rats. These results demonstrate the potential of polymer-based drug delivery devices in the treatment of epilepsy and warrant their investigation in animal models of focal epilepsy. Copyright © 2011 Wiley Periodicals, Inc.

Sequence-dependent effects in drug-DNA interaction: the crystal structure of Hoechst 33258 bound to the d(CGCAAATTTGCG)2 duplex.

PubMed Central

Spink, N; Brown, D G; Skelly, J V; Neidle, S

1994-01-01

The bis-benzimidazole drug Hoechst 33258 has been co-crystallized with the dodecanucleotide sequence d(CGCAAATTTGCG)2. The structure has been solved by molecular replacement and refined to an R factor of 18.5% for 2125 reflections collected on a Xentronics area detector. The drug is bound in the minor groove, at the five base-pair site 5'-ATTTG and is in a unique orientation. This is displaced by one base pair in the 5' direction compared to previously-determined structures of this drug with the sequence d(CGCGAATTCGCG)2. Reasons for this difference in behaviour are discussed in terms of several sequence-dependent structural features of the DNA, with particular reference to differences in propeller twist and minor-groove width. Images PMID:7515488

Effective screening strategy using ensembled pharmacophore models combined with cascade docking: application to p53-MDM2 interaction inhibitors.

PubMed

Xue, Xin; Wei, Jin-Lian; Xu, Li-Li; Xi, Mei-Yang; Xu, Xiao-Li; Liu, Fang; Guo, Xiao-Ke; Wang, Lei; Zhang, Xiao-Jin; Zhang, Ming-Ye; Lu, Meng-Chen; Sun, Hao-Peng; You, Qi-Dong

2013-10-28

Protein-protein interactions (PPIs) play a crucial role in cellular function and form the backbone of almost all biochemical processes. In recent years, protein-protein interaction inhibitors (PPIIs) have represented a treasure trove of potential new drug targets. Unfortunately, there are few successful drugs of PPIIs on the market. Structure-based pharmacophore (SBP) combined with docking has been demonstrated as a useful Virtual Screening (VS) strategy in drug development projects. However, the combination of target complexity and poor binding affinity prediction has thwarted the application of this strategy in the discovery of PPIIs. Here we report an effective VS strategy on p53-MDM2 PPI. First, we built a SBP model based on p53-MDM2 complex cocrystal structures. The model was then simplified by using a Receptor-Ligand complex-based pharmacophore model considering the critical binding features between MDM2 and its small molecular inhibitors. Cascade docking was subsequently applied to improve the hit rate. Based on this strategy, we performed VS on NCI and SPECS databases and successfully discovered 6 novel compounds from 15 hits with the best, compound 1 (NSC 5359), K(i) = 180 ± 50 nM. These compounds can serve as lead compounds for further optimization.

Broad Specificity Efflux pumps and Their Role in Multidrug Resistance of Gram Negative Bacteria

PubMed Central

Nikaido, Hiroshi; Pagès, Jean-Marie

2013-01-01

Antibiotic resistance mechanisms reported in Gram-negative bacteria are producing a worldwide health problem. The continuous dissemination of «multi-drug resistant» (MDR) bacteria drastically reduces the efficacy of our antibiotic “arsenal” and consequently increases the frequency of therapeutic failure. In MDR bacteria, the over-expression of efflux pumps that expel structurally-unrelated drugs contributes to the reduced susceptibility by decreasing the intracellular concentration of antibiotics. During the last decade, several clinical data indicate an increasing involvement of efflux pumps in the emergence and dissemination of resistant Gram-negative bacteria. It is necessary to clearly define the molecular, functional and genetic bases of the efflux pump in order to understand the translocation of antibiotic molecules through the efflux transporter. The recent investigation on the efflux pump AcrB at its structural and physiological level, including the identification of drug affinity sites and kinetic parameters for various antibiotics, may open the way to rationally develop an improved new generation of antibacterial agents as well as efflux inhibitors in order to efficiently combat efflux-based resistance mechanisms. PMID:21707670

Synthesis and structural characterization of some trisulfide analoges of thiouracil-based antithyroid drugs

NASA Astrophysics Data System (ADS)

Bhabak, Krishna P.; Bhowmick, Debasish

2012-08-01

Thiourea-based antithyroid drugs are effectively used for the treatment of hyperthyroidism. In this paper, we describe the synthesis of new trisulfides (11-12) from the commonly used thiourea-based antithyroid drugs such as 6-n-propyl-2-thiouracil (PTU) and 6-methyl-2-thiouracil (MTU) in the reaction with I2/KI system. Structural analysis by single crystal X-ray diffraction studies revealed the stabilization of trisulfides by a lactam-lactim tautomerism facilitating effective intramolecular as well as intermolecular non-covalent interactions. Although the structures of both trisulfides were found to be quite similar, a notable difference in the intermolecular interactions was observed between compounds 11 and 12 leading to different structural patterns. Structural stabilization of these trisulfides by tautomerism followed by intramolecular as well as intermolecular H-bonds makes these molecules as perfect examples in molecular recognition with self-complementary donor and acceptor units within a single molecule.

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment

PubMed Central

2010-01-01

Background Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. Results We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. Conclusions In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets. PMID:21034488

Structural modelling and comparative analysis of homologous, analogous and specific proteins from Trypanosoma cruzi versus Homo sapiens: putative drug targets for chagas' disease treatment.

PubMed

Capriles, Priscila V S Z; Guimarães, Ana C R; Otto, Thomas D; Miranda, Antonio B; Dardenne, Laurent E; Degrave, Wim M

2010-10-29

Trypanosoma cruzi is the etiological agent of Chagas' disease, an endemic infection that causes thousands of deaths every year in Latin America. Therapeutic options remain inefficient, demanding the search for new drugs and/or new molecular targets. Such efforts can focus on proteins that are specific to the parasite, but analogous enzymes and enzymes with a three-dimensional (3D) structure sufficiently different from the corresponding host proteins may represent equally interesting targets. In order to find these targets we used the workflows MHOLline and AnEnΠ obtaining 3D models from homologous, analogous and specific proteins of Trypanosoma cruzi versus Homo sapiens. We applied genome wide comparative modelling techniques to obtain 3D models for 3,286 predicted proteins of T. cruzi. In combination with comparative genome analysis to Homo sapiens, we were able to identify a subset of 397 enzyme sequences, of which 356 are homologous, 3 analogous and 38 specific to the parasite. In this work, we present a set of 397 enzyme models of T. cruzi that can constitute potential structure-based drug targets to be investigated for the development of new strategies to fight Chagas' disease. The strategies presented here support the concept of structural analysis in conjunction with protein functional analysis as an interesting computational methodology to detect potential targets for structure-based rational drug design. For example, 2,4-dienoyl-CoA reductase (EC 1.3.1.34) and triacylglycerol lipase (EC 3.1.1.3), classified as analogous proteins in relation to H. sapiens enzymes, were identified as new potential molecular targets.

Non-amine-based dopamine transporter (reuptake) inhibitors retain properties of amine-based progenitors.

PubMed

Madras, Bertha K; Fahey, Michele A; Miller, Gregory M; De La Garza, Richard; Goulet, Martin; Spealman, Roger D; Meltzer, Peter C; George, Susan R; O'Dowd, Brian F; Bonab, Ali A; Livni, Eli; Fischman, Alan J

2003-10-31

Without exception, therapeutic and addictive drugs that produce their primary effects by blocking monoamine transporters in brain contain an amine nitrogen in their structure. This fundamental canon of drug design was based on a prevailing premise that an amine nitrogen is required to mimic the structures of monoamine neurotransmitters and other natural products. Non-amines, a novel class of compounds that contain no amine nitrogen, block monoamine transporters in the nM range and display markedly high selectivity for monoamine transporters, but not for receptors. Non-amines retain the spectrum of biochemical and pharmacological properties characteristic of amine-bearing counterparts. These novel drugs compel a revision of current concepts of drug-monoamine transporter complex formation and open avenues for discovery of a new generation of therapeutic drugs.

The Curious Case of the OZ439 Mesylate Salt: An Amphiphilic Antimalarial Drug with Diverse Solution and Solid State Structures.

PubMed

Clulow, Andrew J; Salim, Malinda; Hawley, Adrian; Gilbert, Elliot P; Boyd, Ben J

2018-05-07

Efforts to develop orally administered drugs tend to place an exceptional focus on aqueous solubility as this is an essential criterion for their absorption in the gastrointestinal tract. In this work we examine the solid state behavior and solubility of OZ439, a promising single-dose cure for malaria being developed as the highly water-soluble mesylate salt. The aqueous phase behavior of the OZ439 mesylate salt was determined using a combination of small angle neutron and X-ray scattering (SANS and SAXS, respectively). It was found that this salt has low solubility at low concentrations with the drug largely precipitated in free base aggregates. However, with increasing concentration these crystalline aggregates were observed to dissociate into cationic micelles and lamellar phases, effectively increasing the dissolved drug concentration. It was also found that the dissolved OZ439 spontaneously precipitated in the presence of biologically relevant anions, which we attribute to the high lattice energies of most of the salt forms of the drug. These findings show that aqueous solubility is not always what it seems in the context of amphiphilic drug molecules and highlights that its use as the principal metric in selecting drug candidates for development can be perilous.

hERGCentral: a large database to store, retrieve, and analyze compound-human Ether-à-go-go related gene channel interactions to facilitate cardiotoxicity assessment in drug development.

PubMed

Du, Fang; Yu, Haibo; Zou, Beiyan; Babcock, Joseph; Long, Shunyou; Li, Min

2011-12-01

The unintended and often promiscous inhibition of the cardiac human Ether-à-go-go related gene (hERG) potassium channel is a common cause for either delay or removal of therapeutic compounds from development and withdrawal of marketed drugs. The clinical manifestion is prolongation of the duration between QRS complex and T-wave measured by surface electrocardiogram (ECG)-hence Long QT Syndrome. There are several useful online resources documenting hERG inhibition by known drugs and bioactives. However, their utilities remain somewhat limited because they are biased toward well-studied compounds and their number of data points tends to be much smaller than many commercial compound libraries. The hERGCentral ( www.hergcentral.org ) is mainly based on experimental data obtained from a primary screen by electrophysiology against more than 300,000 structurally diverse compounds. The system is aimed to display and combine three resources: primary electrophysiological data, literature, as well as online reports and chemical library collections. Currently, hERGCentral has annotated datasets of more than 300,000 compounds including structures and chemophysiological properties of compounds, raw traces, and biophysical properties. The system enables a variety of query formats, including searches for hERG effects according to either chemical structure or properties, and alternatively according to the specific biophysical properties of current changes caused by a compound. Therefore, the hERGCentral, as a unique and evolving resource, will facilitate investigation of chemically induced hERG inhibition and therefore drug development. © MARY ANN LIEBERT, INC.

hERGCentral: A Large Database to Store, Retrieve, and Analyze Compound-Human Ether-à-go-go Related Gene Channel Interactions to Facilitate Cardiotoxicity Assessment in Drug Development

PubMed Central

Du, Fang; Yu, Haibo; Zou, Beiyan; Babcock, Joseph; Long, Shunyou

2011-01-01

Abstract The unintended and often promiscous inhibition of the cardiac human Ether-à-go-go related gene (hERG) potassium channel is a common cause for either delay or removal of therapeutic compounds from development and withdrawal of marketed drugs. The clinical manifestion is prolongation of the duration between QRS complex and T-wave measured by surface electrocardiogram (ECG)—hence Long QT Syndrome. There are several useful online resources documenting hERG inhibition by known drugs and bioactives. However, their utilities remain somewhat limited because they are biased toward well-studied compounds and their number of data points tends to be much smaller than many commercial compound libraries. The hERGCentral (www.hergcentral.org) is mainly based on experimental data obtained from a primary screen by electrophysiology against more than 300,000 structurally diverse compounds. The system is aimed to display and combine three resources: primary electrophysiological data, literature, as well as online reports and chemical library collections. Currently, hERGCentral has annotated datasets of more than 300,000 compounds including structures and chemophysiological properties of compounds, raw traces, and biophysical properties. The system enables a variety of query formats, including searches for hERG effects according to either chemical structure or properties, and alternatively according to the specific biophysical properties of current changes caused by a compound. Therefore, the hERGCentral, as a unique and evolving resource, will facilitate investigation of chemically induced hERG inhibition and therefore drug development. PMID:22149888

Antimycobacterial Metabolites from Marine Invertebrates.

PubMed

Daletos, Georgios; Ancheeva, Elena; Chaidir, Chaidir; Kalscheuer, Rainer; Proksch, Peter

2016-10-01

Marine organisms play an important role in natural product-based drug research due to accumulation of structurally unique and bioactive metabolites. The exploration of marine-derived compounds may significantly extend the scientific knowledge of potential scaffolds for antibiotic drug discovery. Development of novel antitubercular agents is especially significant as the emergence of drug-resistant Mycobacterium tuberculosis strains remains threateningly high. Marine invertebrates (i.e., sponges, corals, gorgonians) as a source of new chemical entities are the center of research for several scientific groups, and the wide spectrum of biological activities of marine-derived compounds encourages scientists to carry out investigations in the field of antibiotic research, including tuberculosis treatment. The present review covers published data on antitubercular natural products from marine invertebrates grouped according to their biogenetic origin. Studies on the structure-activity relationships of these important leads are highlighted as well. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance of Machine Learning Algorithms for Qualitative and Quantitative Prediction Drug Blockade of hERG1 channel.

PubMed

Wacker, Soren; Noskov, Sergei Yu

2018-05-01

Drug-induced abnormal heart rhythm known as Torsades de Pointes (TdP) is a potential lethal ventricular tachycardia found in many patients. Even newly released anti-arrhythmic drugs, like ivabradine with HCN channel as a primary target, block the hERG potassium current in overlapping concentration interval. Promiscuous drug block to hERG channel may potentially lead to perturbation of the action potential duration (APD) and TdP, especially when with combined with polypharmacy and/or electrolyte disturbances. The example of novel anti-arrhythmic ivabradine illustrates clinically important and ongoing deficit in drug design and warrants for better screening methods. There is an urgent need to develop new approaches for rapid and accurate assessment of how drugs with complex interactions and multiple subcellular targets can predispose or protect from drug-induced TdP. One of the unexpected outcomes of compulsory hERG screening implemented in USA and European Union resulted in large datasets of IC 50 values for various molecules entering the market. The abundant data allows now to construct predictive machine-learning (ML) models. Novel ML algorithms and techniques promise better accuracy in determining IC 50 values of hERG blockade that is comparable or surpassing that of the earlier QSAR or molecular modeling technique. To test the performance of modern ML techniques, we have developed a computational platform integrating various workflows for quantitative structure activity relationship (QSAR) models using data from the ChEMBL database. To establish predictive powers of ML-based algorithms we computed IC 50 values for large dataset of molecules and compared it to automated patch clamp system for a large dataset of hERG blocking and non-blocking drugs, an industry gold standard in studies of cardiotoxicity. The optimal protocol with high sensitivity and predictive power is based on the novel eXtreme gradient boosting (XGBoost) algorithm. The ML-platform with XGBoost displays excellent performance with a coefficient of determination of up to R 2 ~0.8 for pIC 50 values in evaluation datasets, surpassing other metrics and approaches available in literature. Ultimately, the ML-based platform developed in our work is a scalable framework with automation potential to interact with other developing technologies in cardiotoxicity field, including high-throughput electrophysiology measurements delivering large datasets of profiled drugs, rapid synthesis and drug development via progress in synthetic biology.

RNA secondary structure prediction using soft computing.

PubMed

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

High-field MRS in clinical drug development.

PubMed

Ross, Brian D

2013-07-01

Magnetic resonance spectroscopy (MRS) will continue to play an ever increasing role in drug discovery because MRS does readily define biomarkers for several hundreds of clinically distinct diseases. Published evidence based medicine (EBM) surveys, which generally conclude the opposite, are seriously flawed and do a disservice to the field of drug discovery. This article presents MRS and how it has guided several hundreds of practical human 'drug discovery' endeavors since its development. Specifically, the author looks at the process of 'reverse-translation' and its influence in the expansion of the number of preclinical drug discoveries from in vivo MRS. The author also provides a structured approach of eight criteria, including EBM acceptance, which could potentially re-open the field of MRS for productive exploration of existing and repurposed drugs and cost-effective drug-discovery. MRS-guided drug discovery is poised for future expansion. The cost of clinical trials has escalated and the use of biomarkers has become increasingly useful in improving patient selection for drug trials. Clinical MRS has uncovered a treasure-trove of novel biomarkers and clinical MRS itself has become better standardized and more widely available on 'routine' clinical MRI scanners. When combined with available new MRI sequences, MRS can provide a 'one stop shop' with multiple potential outcome measures for the disease and the drug in question.

Structure-Guided Lead Optimization of Triazolopyrimidine-Ring Substituents Identifies Potent Plasmodium falciparum Dihydroorotate Dehydrogenase Inhibitors with Clinical Candidate Potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coteron, Jose M.; Marco, Maria; Esquivias, Jorge

2012-02-27

Drug therapy is the mainstay of antimalarial therapy, yet current drugs are threatened by the development of resistance. In an effort to identify new potential antimalarials, we have undertaken a lead optimization program around our previously identified triazolopyrimidine-based series of Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) inhibitors. The X-ray structure of PfDHODH was used to inform the medicinal chemistry program allowing the identification of a potent and selective inhibitor (DSM265) that acts through DHODH inhibition to kill both sensitive and drug resistant strains of the parasite. This compound has similar potency to chloroquine in the humanized SCID mouse P. falciparum model,more » can be synthesized by a simple route, and rodent pharmacokinetic studies demonstrated it has excellent oral bioavailability, a long half-life and low clearance. These studies have identified the first candidate in the triazolopyrimidine series to meet previously established progression criteria for efficacy and ADME properties, justifying further development of this compound toward clinical candidate status.« less

Combinatorially-generated library of 6-fluoroquinolone analogs as potential novel antitubercular agents: a chemometric and molecular modeling assessment.

PubMed

Minovski, Nikola; Perdih, Andrej; Solmajer, Tom

2012-05-01

The virtual combinatorial chemistry approach as a methodology for generating chemical libraries of structurally-similar analogs in a virtual environment was employed for building a general mixed virtual combinatorial library with a total of 53.871 6-FQ structural analogs, introducing the real synthetic pathways of three well known 6-FQ inhibitors. The druggability properties of the generated combinatorial 6-FQs were assessed using an in-house developed drug-likeness filter integrating the Lipinski/Veber rule-sets. The compounds recognized as drug-like were used as an external set for prediction of the biological activity values using a neural-networks (NN) model based on an experimentally-determined set of active 6-FQs. Furthermore, a subset of compounds was extracted from the pool of drug-like 6-FQs, with predicted biological activity, and subsequently used in virtual screening (VS) campaign combining pharmacophore modeling and molecular docking studies. This complex scheme, a powerful combination of chemometric and molecular modeling approaches provided novel QSAR guidelines that could aid in the further lead development of 6-FQs agents.

Impact of Chemical Structure on Conjunctival Drug Permeability: Adopting Porcine Conjunctiva and Cassette Dosing for Construction of In Silico Model.

PubMed

Ramsay, Eva; Ruponen, Marika; Picardat, Théo; Tengvall, Unni; Tuomainen, Marjo; Auriola, Seppo; Toropainen, Elisa; Urtti, Arto; Del Amo, Eva M

2017-09-01

Conjunctiva occupies most of the ocular surface area, and conjunctival permeability affects ocular and systemic drug absorption of topical ocular medications. Therefore, the aim of this study was to obtain a computational in silico model for structure-based prediction of conjunctival drug permeability. This was done by employing cassette dosing and quantitative structure-property relationship (QSPR) approach. Permeability studies were performed ex vivo across fresh porcine conjunctiva and simultaneous dosing of a cassette mixture composed of 32 clinically relevant drug molecules with wide chemical space. The apparent permeability values were obtained using drug concentrations that were quantified with liquid chromatography tandem-mass spectrometry. The experimental data were utilized for building a QSPR model for conjunctival permeability predictions. The conjunctival permeability values presented a 17-fold range (0.63-10.74 × 10 -6 cm/s). The final QSPR had a Q 2 value of 0.62 and predicted the external test set with a mean fold error of 1.34. The polar surface area, hydrogen bond donor, and halogen ratio were the most relevant descriptors for defining conjunctival permeability. This work presents for the first time a predictive QSPR model of conjunctival drug permeability and a comprehensive description on conjunctival isolation from the porcine eye. The model can be used for developing new ocular drugs. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

FUNCTIONAL ANALYSIS OF A NOVEL POSITIVE ALLOSTERIC MODULATOR OF AMPA RECEPTORS DERIVED FROM A STRUCTURE-BASED DRUG DESIGN STRATEGY

PubMed Central

Harms, Jonathan E.; Benveniste, Morris; Maclean, John K. F.; Partin, Kathryn M.; Jamieson, Craig

2012-01-01

Positive allosteric modulators of α-amino-3-hydroxy-5-methyl-isoxazole-propionic acid (AMPA) receptors facilitate synaptic plasticity and can improve various forms of learning and memory. These modulators show promise as therapeutic agents for the treatment of neurological disorders such as schizophrenia, ADHD, and mental depression. Three classes of positive modulator, the benzamides, the thiadiazides, and the biarylsulfonamides differentially occupy a solvent accessible binding pocket at the interface between the two subunits that form the AMPA receptor ligand-binding pocket. Here, we describe the electrophysiological properties of a new chemotype derived from a structure-based drug design strategy (SBDD), which makes similar receptor interactions compared to previously reported classes of modulator. This pyrazole amide derivative, JAMI1001A, with a promising developability profile, efficaciously modulates AMPA receptor deactivation and desensitization of both flip and flop receptor isoforms. PMID:22735771

A machine-learned computational functional genomics-based approach to drug classification.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-12-01

The public accessibility of "big data" about the molecular targets of drugs and the biological functions of genes allows novel data science-based approaches to pharmacology that link drugs directly with their effects on pathophysiologic processes. This provides a phenotypic path to drug discovery and repurposing. This paper compares the performance of a functional genomics-based criterion to the traditional drug target-based classification. Knowledge discovery in the DrugBank and Gene Ontology databases allowed the construction of a "drug target versus biological process" matrix as a combination of "drug versus genes" and "genes versus biological processes" matrices. As a canonical example, such matrices were constructed for classical analgesic drugs. These matrices were projected onto a toroid grid of 50 × 82 artificial neurons using a self-organizing map (SOM). The distance, respectively, cluster structure of the high-dimensional feature space of the matrices was visualized on top of this SOM using a U-matrix. The cluster structure emerging on the U-matrix provided a correct classification of the analgesics into two main classes of opioid and non-opioid analgesics. The classification was flawless with both the functional genomics and the traditional target-based criterion. The functional genomics approach inherently included the drugs' modulatory effects on biological processes. The main pharmacological actions known from pharmacological science were captures, e.g., actions on lipid signaling for non-opioid analgesics that comprised many NSAIDs and actions on neuronal signal transmission for opioid analgesics. Using machine-learned techniques for computational drug classification in a comparative assessment, a functional genomics-based criterion was found to be similarly suitable for drug classification as the traditional target-based criterion. This supports a utility of functional genomics-based approaches to computational system pharmacology for drug discovery and repurposing.

The Primary Mechanism of Cellular Internalization for a Short Cell- Penetrating Peptide as a Nano-Scale Delivery System.

PubMed

Liu, Betty R; Huang, Yue-Wern; Korivi, Mallikarjuna; Lo, Shih-Yen; Aronstam, Robert S; Lee, Han-Jung

2017-01-01

Development of effective drug delivery systems (DDS) is a critical issue in health care and medicine. Advances in molecular biology and nanotechnology have allowed the introduction of nanomaterial-based drug delivery systems. Cell-penetrating peptides (CPPs) can form the basis of drug delivery systems by virtue of their ability to support the transport of cargoes into the cell. Potential cargoes include proteins, DNA, RNA, liposomes, and nanomaterials. These cargoes generally retain their bioactivities upon entering cells. In the present study, the smallest, fully-active lactoferricin-derived CPP, L5a is used to demonstrate the primary contributor of cellular internalization. The secondary helical structure of L5a encompasses symmetrical positive charges around the periphery. The contributions of cell-specificity, peptide length, concentration, zeta potential, particle size, and spatial structure of the peptides were examined, but only zeta potential and spatial structure affected protein transduction efficiency. FITC-labeled L5a appeared to enter cells via direct membrane translocation insofar as endocytic modulators did not block FITC-L5a entry. This is the same mechanism of protein transduction active in Cy5 labeled DNA delivery mediated by FITC-L5a. A significant reduction of transduction efficiency was observed with structurally incomplete FITC-L5a formed by tryptic destruction, in which case the mechanism of internalization switched to a classical energydependent endocytosis pathway. These results support the continued development of the non-cytotoxic L5a as an efficient tool for drug delivery. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Advanced mass spectrometry-based methods for the analysis of conformational integrity of biopharmaceutical products

PubMed Central

Bobst, Cedric E.; Kaltashov, Igor A.

2012-01-01

Mass spectrometry has already become an indispensable tool in the analytical armamentarium of the biopharmaceutical industry, although its current uses are limited to characterization of covalent structure of recombinant protein drugs. However, the scope of applications of mass spectrometry-based methods is beginning to expand to include characterization of the higher order structure and dynamics of biopharmaceutical products, a development which is catalyzed by the recent progress in mass spectrometry-based methods to study higher order protein structure. The two particularly promising methods that are likely to have the most significant and lasting impact in many areas of biopharmaceutical analysis, direct ESI MS and hydrogen/deuterium exchange, are focus of this article. PMID:21542797

Drug addicts treatment motivations: perception of family members.

PubMed

Ferreira, Aline Cristina Zerwes; Capistrano, Fernanda Carolina; de Souza, Edice Bueno; Borba, Letícia de Oliveira; Kalinke, Luciana Puchalski; Maftum, Mariluci Alves

2015-01-01

to identify the reasons and motivations why family members search treatment for the drug addicted. descriptive qualitative research, developed in 2012 and 2013, in a Drug Addicts Rehabilitation Unit of Parana State, Brazil. A total of 19 semi-structured interviews were conducted with the drug addicts' family members in treatment. The results were analyzed based on the Transtheoretical Model of Behavior Change and organized in thematic categories according with qualitative data analysis. the search for treatment for drug addicts occurred: in the pre-contemplation stage influenced by external factors; in the contemplation stage both for ambivalence and behavioral changes needs; in the action stage by awareness of drug addiction and also professional help needs; and in the maintenance stage because of the non-conservation of behavioral changes. an evaluation of motivational stages in the beginning of treatment is required for expansion of success possibilities in the rehabilitation process.

Solid Lipid Nanoparticles and Nanostructured Lipid Carriers: Structure, Preparation and Application

PubMed Central

Naseri, Neda; Valizadeh, Hadi; Zakeri-Milani, Parvin

2015-01-01

Lipid nanoparticles (LNPs) have attracted special interest during last few decades. Solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) are two major types of Lipid-based nanoparticles. SLNs were developed to overcome the limitations of other colloidal carriers, such as emulsions, liposomes and polymeric nanoparticles because they have advantages like good release profile and targeted drug delivery with excellent physical stability. In the next generation of the lipid nanoparticle, NLCs are modified SLNs which improve the stability and capacity loading. Three structural models of NLCs have been proposed. These LNPs have potential applications in drug delivery field, research, cosmetics, clinical medicine, etc. This article focuses on features, structure and innovation of LNPs and presents a wide discussion about preparation methods, advantages, disadvantages and applications of LNPs by focusing on SLNs and NLCs. PMID:26504751

Accurate de novo design of hyperstable constrained peptides

PubMed Central

Bhardwaj, Gaurav; Mulligan, Vikram Khipple; Bahl, Christopher D.; Gilmore, Jason M.; Harvey, Peta J.; Cheneval, Olivier; Buchko, Garry W.; Pulavarti, Surya V.S.R.K.; Kaas, Quentin; Eletsky, Alexander; Huang, Po-Ssu; Johnsen, William A.; Greisen, Per; Rocklin, Gabriel J.; Song, Yifan; Linsky, Thomas W.; Watkins, Andrew; Rettie, Stephen A.; Xu, Xianzhong; Carter, Lauren P.; Bonneau, Richard; Olson, James M.; Coutsias, Evangelos; Correnti, Colin E.; Szyperski, Thomas; Craik, David J.; Baker, David

2016-01-01

Summary Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for de novo design of conformationally-restricted peptides, and the use of these methods to design 15–50 residue disulfide-crosslinked and heterochiral N-C backbone-cyclized peptides. These peptides are exceptionally stable to thermal and chemical denaturation, and twelve experimentally-determined X-ray and NMR structures are nearly identical to the computational models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs. PMID:27626386

Insight into the Mechanism of Hydrolysis of Meropenem by OXA-23 Serine-β-lactamase Gained by Quantum Mechanics/Molecular Mechanics Calculations.

PubMed

Sgrignani, Jacopo; Grazioso, Giovanni; De Amici, Marco

2016-09-13

The fast and constant development of drug resistant bacteria represents a serious medical emergency. To overcome this problem, the development of drugs with new structures and modes of action is urgently needed. In this work, we investigated, at the atomistic level, the mechanisms of hydrolysis of Meropenem by OXA-23, a class D β-lactamase, combining unbiased classical molecular dynamics and umbrella sampling simulations with classical force field-based and quantum mechanics/molecular mechanics potentials. Our calculations provide a detailed structural and dynamic picture of the molecular steps leading to the formation of the Meropenem-OXA-23 covalent adduct, the subsequent hydrolysis, and the final release of the inactive antibiotic. In this mechanistic framework, the predicted activation energy is in good agreement with experimental kinetic measurements, validating the expected reaction path.

Systematic drug repositioning for a wide range of diseases with integrative analyses of phenotypic and molecular data.

PubMed

Iwata, Hiroaki; Sawada, Ryusuke; Mizutani, Sayaka; Yamanishi, Yoshihiro

2015-02-23

Drug repositioning, or the application of known drugs to new indications, is a challenging issue in pharmaceutical science. In this study, we developed a new computational method to predict unknown drug indications for systematic drug repositioning in a framework of supervised network inference. We defined a descriptor for each drug-disease pair based on the phenotypic features of drugs (e.g., medicinal effects and side effects) and various molecular features of diseases (e.g., disease-causing genes, diagnostic markers, disease-related pathways, and environmental factors) and constructed a statistical model to predict new drug-disease associations for a wide range of diseases in the International Classification of Diseases. Our results show that the proposed method outperforms previous methods in terms of accuracy and applicability, and its performance does not depend on drug chemical structure similarity. Finally, we performed a comprehensive prediction of a drug-disease association network consisting of 2349 drugs and 858 diseases and described biologically meaningful examples of newly predicted drug indications for several types of cancers and nonhereditary diseases.

Discovery of 1-(3-aryl-4-chlorophenyl)-3-(p-aryl)urea derivatives against breast cancer by inhibiting PI3K/Akt/mTOR and Hedgehog signalings.

PubMed

Li, Wenlu; Sun, Qinsheng; Song, Lu; Gao, Chunmei; Liu, Feng; Chen, Yuzong; Jiang, Yuyang

2017-12-01

PI3K/Akt/mTOR and hedgehog (Hh) signalings are two important pathways in breast cancer, which are usually connected with the drug resistance and cancer migration. Many studies indicated that PI3K/Akt/mTOR inhibitors and Hh inhibitors displayed synergistic effects, and the combination of the two signaling drugs could delay drug resistance and inhibit cancer migration in breast cancer. Therefore, the development of molecules simultaneously inhibiting these two pathways is urgent needed. Based on the structures of PI3K inhibitor buparlisib and Hh inhibitor vismodegib, a series of hybrid structures were designed and synthesized utilizing rational drug design and computer-based drug design. Several compounds displayed excellent antiproliferative activities against several breast cancer cell lines, including triple-negative breast cancer (TNBC) MDA-MB-231 cell. Further mechanistic studies demonstrated that the representative compound 9i could inhibit both PI3K/Akt/mTOR and hedgehog (Hh) signalings by inhibiting the phosphorylation of S6K and Akt as well as decreasing the SAG elevated expression of Gli1. Compound 9i could also induce apoptosis remarkably in T47D and MDA-MB-231 cells. In the transwell assay, 9i showed significant inhibition on the migration of MDA-MB-231. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Diagnostic accuracy of a two-item Drug Abuse Screening Test (DAST-2).

PubMed

Tiet, Quyen Q; Leyva, Yani E; Moos, Rudolf H; Smith, Brandy

2017-11-01

Drug use is prevalent and costly to society, but individuals with drug use disorders (DUDs) are under-diagnosed and under-treated, particularly in primary care (PC) settings. Drug screening instruments have been developed to identify patients with DUDs and facilitate treatment. The Drug Abuse Screening Test (DAST) is one of the most well-known drug screening instruments. However, similar to many such instruments, it is too long for routine use in busy PC settings. This study developed and validated a briefer and more practical DAST for busy PC settings. We recruited 1300 PC patients in two Department of Veterans Affairs (VA) clinics. Participants responded to a structured diagnostic interview. We randomly selected half of the sample to develop and the other half to validate the new instrument. We employed signal detection techniques to select the best DAST items to identify DUDs (based on the MINI) and negative consequences of drug use (measured by the Inventory of Drug Use Consequences). Performance indicators were calculated. The two-item DAST (DAST-2) was 97% sensitive and 91% specific for DUDs in the development sample and 95% sensitive and 89% specific in the validation sample. It was highly sensitive and specific for DUD and negative consequences of drug use in subgroups of patients, including gender, age, race/ethnicity, marital status, educational level, and posttraumatic stress disorder status. The DAST-2 is an appropriate drug screening instrument for routine use in PC settings in the VA and may be applicable in broader range of PC clinics. Published by Elsevier Ltd.

Found in translation: how preclinical research is guiding the clinical development of the BCL-2-selective inhibitor venetoclax

PubMed Central

Leverson, Joel D.; Sampath, Deepak; Souers, Andrew J.; Rosenberg, Saul H.; Fairbrother, Wayne J.; Amiot, Martine; Konopleva, Marina; Letai, Anthony

2017-01-01

Since the discovery of apoptosis as a form of programmed cell death, targeting the apoptosis pathway to induce cancer cell death has been a high priority goal for cancer therapy. After decades of effort, drug discovery scientists have succeeded in generating small-molecule inhibitors of antiapoptotic BCL-2 family proteins. Innovative medicinal chemistry and structure-based drug design, coupled with a strong fundamental understanding of BCL-2 biology, were essential to the development of BH3 mimetics such as the BCL-2-selective inhibitor venetoclax. We review a number of preclinical studies that have deepened our understanding of BCL-2 biology and facilitated the clinical development of venetoclax. PMID:29146569

Program Administration | Division of Cancer Prevention

Cancer.gov

Governance Structure Recognizing the importance of an integrated approach to preventative drug development, there is a unified Governance Structure for the PREVENT Program responsible for coordinating and integrating available resources. With the goal of reaching go/no-go decisions as efficiently as possible, the purpose is to ensure a pragmatic approach to drug development

Controlled and extended drug release behavior of chitosan-based nanoparticle carrier.

PubMed

Yuan, Q; Shah, J; Hein, S; Misra, R D K

2010-03-01

Controlled drug release is presently gaining significant attention. In this regard, we describe here the synthesis (based on the understanding of chemical structure), structural morphology, swelling behavior and drug release response of chitosan intercalated in an expandable layered aluminosilicate. In contrast to pure chitosan, for which there is a continuous increase in drug release with time, the chitosan-aluminosilicate nanocomposite carrier was characterized by controlled and extended release. Drug release from the nanocomposite particle carrier occurred by degradation of the carrier to its individual components or nanostructures with a different composition. In both the layered aluminosilicate-based mineral and chitosan-aluminosilicate nanocomposite carriers the positively charged chemotherapeutic drug strongly bound to the negatively charged aluminosilicate and release of the drug was slow. Furthermore, the pattern of drug release from the chitosan-aluminosilicate nanocomposite carrier was affected by pH and the chitosan/aluminosilicate ratio. The study points to the potential application of this hybrid nanocomposite carrier in biomedical applications, including tissue engineering and controlled drug delivery. Copyright 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Microfluidic cell-phoresis enabling high-throughput analysis of red blood cell deformability and biophysical screening of antimalarial drugs.

PubMed

Santoso, Aline T; Deng, Xiaoyan; Lee, Jeong-Hyun; Matthews, Kerryn; Duffy, Simon P; Islamzada, Emel; McFaul, Sarah M; Myrand-Lapierre, Marie-Eve; Ma, Hongshen

2015-12-07

Changes in red blood cell (RBC) deformability are associated with the pathology of many diseases and could potentially be used to evaluate disease status and treatment efficacy. We developed a simple, sensitive, and multiplexed RBC deformability assay based on the spatial dispersion of single cells in structured microchannels. This mechanism is analogous to gel electrophoresis, but instead of transporting molecules through nano-structured material to measure their length, RBCs are transported through micro-structured material to measure their deformability. After transport, the spatial distribution of cells provides a readout similar to intensity bands in gel electrophoresis, enabling simultaneous measurement on multiple samples. We used this approach to study the biophysical signatures of falciparum malaria, for which we demonstrate label-free and calibration-free detection of ring-stage infection, as well as in vitro assessment of antimalarial drug efficacy. We show that clinical antimalarial drugs universally reduce the deformability of RBCs infected by Plasmodium falciparum and that recently discovered PfATP4 inhibitors, known to induce host-mediated parasite clearance, display a distinct biophysical signature. Our process captures key advantages from gel electrophoresis, including image-based readout and multiplexing, to provide a functional screen for new antimalarials and adjunctive agents.

[The activity of drug addiction service of the Russian Federation: an assessment of statistical parameters and an analysis of results].

PubMed

Koshkina, E A; Kirzhanova, V V; Babicheva, L P; Mugantseva, L A

2013-01-01

The authors studied changes in the structure of drug addiction services, the dynamics of outpatient and inpatient referrals for drug addiction treatment and effectiveness of drug addiction services in 2011 compared to the preceding period. There was a reduction of availability of drug treatment services due to the reduction of the number of drug addiction units and the depletion of human resource potential. The lack of structural development of rehabilitation sector of drug care services and low rates of its development as well as the decrease in the number of patients seeking treatment are highlighted. It has been concluded that the drug addiction services require reorganization of its regulatory and legal framework and need innovative organizational and management decisions and human resources trained in innovative thinking and technologies.

Strategy for Identifying Repurposed Drugs for the Treatment of Cerebral Cavernous Malformation

PubMed Central

Gibson, Christopher C.; Zhu, Weiquan; Davis, Chadwick T.; Bowman-Kirigin, Jay A.; Chan, Aubrey C.; Ling, Jing; Walker, Ashley E.; Goitre, Luca; Monache, Simona Delle; Retta, Saverio Francesco; Shiu, Yan-Ting E.; Grossmann, Allie H.; Thomas, Kirk R.; Donato, Anthony J.; Lesniewski, Lisa A.; Whitehead, Kevin J.; Li, Dean Y.

2014-01-01

Background Cerebral cavernous malformation (CCM) is a hemorrhagic stroke disease affecting up to 0.5% of North Americans with no approved non-surgical treatment. A subset of patients have a hereditary form of the disease due primarily to loss-of-function mutations in KRIT1, CCM2, or PDCD10. We sought to identify known drugs that could be repurposed to treat CCM. Methods and Results We developed an unbiased screening platform based on both cellular and animal models of loss-of-function of CCM2. Our discovery strategy consisted of four steps: an automated immunofluorescence and machine-learning-based primary screen of structural phenotypes in human endothelial cells deficient in CCM2; a secondary screen of functional changes in endothelial stability in these same cells; a rapid in vivo tertiary screen of dermal microvascular leak in mice lacking endothelial Ccm2; and finally a quaternary screen of CCM lesion burden in these same mice. We screened 2,100 known drugs and bioactive compounds, and identified two candidates for further study, cholecalciferol (Vitamin D3) and tempol (a scavenger of superoxide). Each drug decreased lesion burden in a mouse model of CCM vascular disease by approximately 50%. Conclusions By identifying known drugs as potential therapeutics for CCM, we have decreased the time, cost, and risk of bringing treatments to patients. Each drug also prompts additional exploration of biomarkers of CCM disease. We further suggest that the structure-function screening platform presented here may be adapted and scaled to facilitate drug discovery for diverse loss-of-function genetic vascular disease. PMID:25486933

Cryptic binding sites on proteins: definition, detection, and druggability.

PubMed

Vajda, Sandor; Beglov, Dmitri; Wakefield, Amanda E; Egbert, Megan; Whitty, Adrian

2018-05-22

Many proteins in their unbound structures lack surface pockets appropriately sized for drug binding. Hence, a variety of experimental and computational tools have been developed for the identification of cryptic sites that are not evident in the unbound protein but form upon ligand binding, and can provide tractable drug target sites. The goal of this review is to discuss the definition, detection, and druggability of such sites, and their potential value for drug discovery. Novel methods based on molecular dynamics simulations are particularly promising and yield a large number of transient pockets, but it has been shown that only a minority of such sites are generally capable of binding ligands with substantial affinity. Based on recent studies, current methodology can be improved by combining molecular dynamics with fragment docking and machine learning approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.

Erythrocytes-based synthetic delivery systems: transition from conventional to novel engineering strategies.

PubMed

Bhateria, Manisha; Rachumallu, Ramakrishna; Singh, Rajbir; Bhatta, Rabi Sankar

2014-08-01

Erythrocytes (red blood cells [RBCs]) and artificial or synthetic delivery systems such as liposomes, nanoparticles (NPs) are the most investigated carrier systems. Herein, progress made from conventional approach of using RBC as delivery systems to novel approach of using synthetic delivery systems based on RBC properties will be reviewed. We aim to highlight both conventional and novel approaches of using RBCs as potential carrier system. Conventional approaches which include two main strategies are: i) directly loading therapeutic moieties in RBCs; and ii) coupling them with RBCs whereas novel approaches exploit structural, mechanical and biological properties of RBCs to design synthetic delivery systems through various engineering strategies. Initial attempts included coupling of antibodies to liposomes to specifically target RBCs. Knowledge obtained from several studies led to the development of RBC membrane derived liposomes (nanoerythrosomes), inspiring future application of RBC or its structural features in other attractive delivery systems (hydrogels, filomicelles, microcapsules, micro- and NPs) for even greater potential. In conclusion, this review dwells upon comparative analysis of various conventional and novel engineering strategies in developing RBC based drug delivery systems, diversifying their applications in arena of drug delivery. Regardless of the challenges in front of us, RBC based delivery systems offer an exciting approach of exploiting biological entities in a multitude of medical applications.

E2 protein cage as a multifunctional nanoplatform

NASA Astrophysics Data System (ADS)

Dalmau Mallorqui, Merce

Caged protein systems such as viral capsids, heat shock proteins, and ferritin are spherical structures that occur naturally in living organisms and are a growing class of biomimetic templates used to create new materials in nanotechnology. Such systems have been proposed as general drug carriers since they form highly symmetric nanoscale architectures that offer the potential to be tailored according to the desired application. Within this framework, this dissertation focuses on the design and development of a new drug delivery nanoplatform based on the E2 subunit of the pyruvate dehydrogenase protein from Bacillus stearothermophilus. This scaffold forms a 25-nm nanocapsule structure with a hollow cavity. We produced a variant of this protein consisting only of the structural core, and found the thermostability of this self-assembled scaffold to be unusually high, with an onset unfolding temperature of 81.1 +/- 0.9°C and an apparent midpoint unfolding temperature of 91.4 +/- 1.4°C. To evaluate the potential of this scaffold for encapsulation of guest molecules in the internal cavity, we made variants which altered the physicochemical properties of the hollow internal surface. These mutants, yielding up to 240 mutations within this cavity, assembled into correct architectures and exhibited high thermostability that was also comparable to the wild-type scaffold. To show the applicability of this scaffold we coupled two drug-like small molecules to the internal cavity. We also developed a new strategy for encapsulation of small hydrophobic drug molecules. This method is based on hydrophobic differences between the interior cavity and the external buffer to nucleate drug-like agents inside the protein cage. We demonstrate that internal mutations can introduce non-native functionality and enable molecular encapsulation within the cavity while still retaining the dodecahedral structure. Another surface amenable to modifications is the interface between subunits. Such a region was modified to introduce pH-dependent scaffold disassembly ability to assist drug release upon endocytosis inside the cells. Moreover, we demonstrated that modulation of the pH at which disassembly occurs can be achieved by modulation of electrostatic interactions through mutagenesis or changing ionic strength. Together, these results demonstrate the potential of our scaffold as a robust nanoscale platform for biomedical applications.

Drug use prevention: factors associated with program implementation in Brazilian urban schools.

PubMed

Pereira, Ana Paula Dias; Sanchez, Zila M

2018-03-07

A school is a learning environment that contributes to the construction of personal values, beliefs, habits and lifestyles, provide convenient settings for the implementation of drug use prevention programs targeting adolescents, who are the population group at highest risk of initiating drug use. The objective of the present study was to investigate the prevalence of factors associated with implementing drug use prevention programs in Brazilian public and private middle and high urban schools. The present population-based cross-sectional survey was conducted with a probability sample of 1151 school administrators stratified by the 5 Brazilian administrative divisions, in 2014. A close-ended, self-reported online questionnaire was used. Logistic regression analysis was used to identify factors associated with implementing drug use prevention programs in schools. A total of 51.1% of the schools had adopted drug use prevention programs. The factors associated with program implementation were as follows: belonging to the public school network; having a library; development of activities targeting sexuality; development of "Health at School Program" activities; offering extracurricular activities; and having an administrator that participated in training courses on drugs. The adoption of drug use prevention practices in Brazilian schools may be expanded with greater orchestration of schools through specialized training of administrators and teachers, expansion of the School Health Program and concomitant development of the schools' structural and curricular attributes.

Understanding the Molecular Determinant of Reversible Human Monoamine Oxidase B Inhibitors Containing 2H-Chromen-2-One Core: Structure-Based and Ligand-Based Derived Three-Dimensional Quantitative Structure-Activity Relationships Predictive Models.

PubMed

Mladenović, Milan; Patsilinakos, Alexandros; Pirolli, Adele; Sabatino, Manuela; Ragno, Rino

2017-04-24

Monoamine oxidase B (MAO B) catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. Consequently, the enzyme's malfunction can induce oxidative damage to mitochondrial DNA and mediates development of Parkinson's disease. Thus, MAO B emerges as a promising target for developing pharmaceuticals potentially useful to treat this vicious neurodegenerative condition. Aiming to contribute to the development of drugs with the reversible mechanism of MAO B inhibition only, herein, an extended in silico-in vitro procedure for the selection of novel MAO B inhibitors is demonstrated, including the following: (1) definition of optimized and validated structure-based three-dimensional (3-D) quantitative structure-activity relationships (QSAR) models derived from available cocrystallized inhibitor-MAO B complexes; (2) elaboration of SAR features for either irreversible or reversible MAO B inhibitors to characterize and improve coumarin-based inhibitor activity (Protein Data Bank ID: 2V61 ) as the most potent reversible lead compound; (3) definition of structure-based (SB) and ligand-based (LB) alignment rule assessments by which virtually any untested potential MAO B inhibitor might be evaluated; (4) predictive ability validation of the best 3-D QSAR model through SB/LB modeling of four coumarin-based external test sets (267 compounds); (5) design and SB/LB alignment of novel coumarin-based scaffolds experimentally validated through synthesis and biological evaluation in vitro. Due to the wide range of molecular diversity within the 3-D QSAR training set and derived features, the selected N probe-derived 3-D QSAR model proves to be a valuable tool for virtual screening (VS) of novel MAO B inhibitors and a platform for design, synthesis and evaluation of novel active structures. Accordingly, six highly active and selective MAO B inhibitors (picomolar to low nanomolar range of activity) were disclosed as a result of rational SB/LB 3D QSAR design; therefore, D123 (IC 50 = 0.83 nM, K i = 0.25 nM) and D124 (IC 50 = 0.97 nM, K i = 0.29 nM) are potential lead candidates as anti-Parkinson's drugs.

Closing the door on flaviviruses: entry as a target for antiviral drug design.

PubMed

Perera, Rushika; Khaliq, Mansoora; Kuhn, Richard J

2008-10-01

With the emergence and rapid spread of West Nile virus in the United States since 1999, and the 50-100 million infections per year caused by dengue virus globally, the threat of flaviviruses as re-emerging human pathogens has become a reality. To support the efforts that are currently being pursued to develop effective vaccines against these viruses, researchers are also actively pursuing the development of small molecule compounds that target various aspects of the virus life cycle. Recent advances in the structural characterization of the flaviviruses have provided a strong foundation towards these efforts. These studies have provided the pseudo-atomic structures of virions from several members of the genus as well as atomic resolution structures of several viral proteins. Most importantly, these studies have highlighted specific structural rearrangements that occur within the virion that are necessary for the virus to complete its life cycle. These rearrangements occur when the virus must transition from immature, to mature, to fusion-active states and rely heavily on the conformational flexibility of the envelope (E) protein that forms the outer glycoprotein shell of the virus. Analysis of these conformational changes can suggest promising targets for structure-based antiviral design. For instance, by targeting the flexibility of the E protein, it might be possible to inhibit required rearrangements of this protein and trap the virus in a specific state. This would interfere with a productive flaviviral infection. This review presents a structural perspective of the flavivirus life cycle and focuses on the role of the E protein as an opportune target for structure-based antiviral drug design.

Multiwell capillarity-based microfluidic device for the study of 3D tumour tissue-2D endothelium interactions and drug screening in co-culture models.

PubMed

Virumbrales-Muñoz, María; Ayuso, José María; Olave, Marta; Monge, Rosa; de Miguel, Diego; Martínez-Lostao, Luis; Le Gac, Séverine; Doblare, Manuel; Ochoa, Ignacio; Fernandez, Luis J

2017-09-20

The tumour microenvironment is very complex, and essential in tumour development and drug resistance. The endothelium is critical in the tumour microenvironment: it provides nutrients and oxygen to the tumour and is essential for systemic drug delivery. Therefore, we report a simple, user-friendly microfluidic device for co-culture of a 3D breast tumour model and a 2D endothelium model for cross-talk and drug delivery studies. First, we demonstrated the endothelium was functional, whereas the tumour model exhibited in vivo features, e.g., oxygen gradients and preferential proliferation of cells with better access to nutrients and oxygen. Next, we observed the endothelium structure lost its integrity in the co-culture. Following this, we evaluated two drug formulations of TRAIL (TNF-related apoptosis inducing ligand): soluble and anchored to a LUV (large unilamellar vesicle). Both diffused through the endothelium, LUV-TRAIL being more efficient in killing tumour cells, showing no effect on the integrity of endothelium. Overall, we have developed a simple capillary force-based microfluidic device for 2D and 3D cell co-cultures. Our device allows high-throughput approaches, patterning different cell types and generating gradients without specialised equipment. We anticipate this microfluidic device will facilitate drug screening in a relevant microenvironment thanks to its simple, effective and user-friendly operation.

Comprehensive computational design of ordered peptide macrocycles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hosseinzadeh, Parisa; Bhardwaj, Gaurav; Mulligan, Vikram Khipple

Mixed chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to-date, but there is currently no way to systematically search through the structural space spanned by such compounds for new drug candidates. Natural proteins do not provide a useful guide: peptide macrocycles lack regular secondary structures and hydrophobic cores and have different backbone torsional constraints. Hence the development of new peptide macrocycles has been approached by modifying natural products or using library selection methods; the former is limited by the small number of known structures, and the latter by the limited size and diversity accessible throughmore » library-based methods. To overcome these limitations, here we enumerate the stable structures that can be adopted by macrocyclic peptides composed of L and D amino acids. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. We synthesize and characterize by NMR twelve 7-10 residue macrocycles, 9 of which have structures very close to the design models in solution. NMR structures of three 11-14 residue bicyclic designs are also very close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide based macrocycles unparalleled for other molecular systems, and vastly increase the available starting scaffolds for both rational drug design and library selection methods.« less

Development of Potent Antiviral Drugs Inspired by Viral Hexameric DNA-Packaging Motors with Revolving Mechanism

PubMed Central

Pi, Fengmei; Zhao, Zhengyi; Chelikani, Venkata; Yoder, Kristine; Kvaratskhelia, Mamuka

2016-01-01

The intracellular parasitic nature of viruses and the emergence of antiviral drug resistance necessitate the development of new potent antiviral drugs. Recently, a method for developing potent inhibitory drugs by targeting biological machines with high stoichiometry and a sequential-action mechanism was described. Inspired by this finding, we reviewed the development of antiviral drugs targeting viral DNA-packaging motors. Inhibiting multisubunit targets with sequential actions resembles breaking one bulb in a series of Christmas lights, which turns off the entire string. Indeed, studies on viral DNA packaging might lead to the development of new antiviral drugs. Recent elucidation of the mechanism of the viral double-stranded DNA (dsDNA)-packaging motor with sequential one-way revolving motion will promote the development of potent antiviral drugs with high specificity and efficiency. Traditionally, biomotors have been classified into two categories: linear and rotation motors. Recently discovered was a third type of biomotor, including the viral DNA-packaging motor, beside the bacterial DNA translocases, that uses a revolving mechanism without rotation. By analogy, rotation resembles the Earth's rotation on its own axis, while revolving resembles the Earth's revolving around the Sun (see animations at http://rnanano.osu.edu/movie.html). Herein, we review the structures of viral dsDNA-packaging motors, the stoichiometries of motor components, and the motion mechanisms of the motors. All viral dsDNA-packaging motors, including those of dsDNA/dsRNA bacteriophages, adenoviruses, poxviruses, herpesviruses, mimiviruses, megaviruses, pandoraviruses, and pithoviruses, contain a high-stoichiometry machine composed of multiple components that work cooperatively and sequentially. Thus, it is an ideal target for potent drug development based on the power function of the stoichiometries of target complexes that work sequentially. PMID:27356896

Phosphodiesterase inhibitors as a new generation of antiprotozoan drugs: exploiting the benefit of enzymes that are highly conserved between host and parasite

PubMed Central

Seebeck, Thomas; Sterk, Geert Jan; Ke, Hengming

2011-01-01

Protozoan infections remain a major unsolved medical problem in many parts of our world. A major obstacle to their treatment is the blatant lack of medication that is affordable, effective, safe and easy to administer. For some of these diseases, including human sleeping sickness, very few compounds are available, many of them old and all of them fraught with toxic side effects. We explore a new concept for developing new-generation antiprotozoan drugs that are based on phosphodiesterase (PDE) inhibitors. Such inhibitors are already used extensively in human pharmacology. Given the high degree of structural similarity between the human and the protozoan PDEs, the vast expertise available in the human field can now be applied to developing disease-specific PDE inhibitors as new antiprotozoan drugs. PMID:21859303

Structure-activity relationship of chemical penetration enhancers in transdermal drug delivery.

PubMed

Kanikkannan, N; Kandimalla, K; Lamba, S S; Singh, M

2000-06-01

Transdermal drug delivery (TDD) is the administration of therapeutic agents through intact skin for systemic effect. TDD offers several advantages over the conventional dosage forms such as tablets, capsules and injections. Currently there are about eight drugs marketed as transdermal patches. Examples of such products include nitroglycerin (angina pectoris), clonidine (hypertension), scopolamine (motion sickness), nicotine (smoking cessation), fentanil (pain) and estradiol (estrogen deficiency). Since skin is an excellent barrier for drug transport, only potent drugs with appropriate physicochemical properties (low molecular weight, adequate solubility in aqueous and non-aqueous solvents, etc) are suitable candidates for transdermal delivery. Penetration enhancement technology is a challenging development that would increase significantly the number of drugs available for transdermal administration. The permeation of drugs through skin can be enhanced by physical methods such as iontophoresis (application of low level electric current) and phonophoresis (use of ultra sound energy) and by chemical penetration enhancers (CPE). In this review, we have discussed about the CPE which have been investigated for TDD. CPE are compounds that enhance the permeation of drugs across the skin. The CPE increase skin permeability by reversibly altering the physicochemical nature of the stratum corneum, the outer most layer of skin, to reduce its diffusional resistance. These compounds increase skin permeability also by increasing the partition coefficient of the drug into the skin and by increasing the thermodynamic activity of the drug in the vehicle. This review compiles the various CPE used for the enhancement of TDD, the mechanism of action of different chemical enhancers and the structure-activity relationship of selected and extensively studied enhancers such as fatty acids, fatty alcohols and terpenes. Based on the chemical structure of penetration enhancers (such as chain length, polarity, level of unsaturation and presence of some special groups such as ketones), the interaction between the stratum corneum and penetration enhancers may vary which will result in significant differences in penetration enhancement. Our review also discusses the various factors to be considered in the selection of an appropriate penetration enhancer for the development of transdermal delivery systems.

Protein-Based Nanomedicine Platforms for Drug Delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma Ham, Aihui; Tang, Zhiwen; Wu, Hong

2009-08-03

Drug delivery systems have been developed for many years, however some limitations still hurdle the pace of going to clinical phase, for example, poor biodistribution, drug molecule cytotoxicity, tissue damage, quick clearance from the circulation system, solubility and stability of drug molecules. To overcome the limitations of drug delivery, biomaterials have to be developed and applied to drug delivery to protect the drug molecules and to enhance the drug’s efficacy. Protein-based nanomedicine platforms for drug delivery are platforms comprised of naturally self-assembled protein subunits of the same protein or a combination of proteins making up a complete system. They aremore » ideal for drug delivery platforms due to their biocompatibility and biodegradability coupled with low toxicity. A variety of proteins have been used and characterized for drug delivery systems including the ferritin/apoferritin protein cage, plant derived viral capsids, the small Heat shock protein (sHsp) cage, albumin, soy and whey protein, collagen, and gelatin. There are many different types and shapes that have been prepared to deliver drug molecules using protein-based platforms including the various protein cages, microspheres, nanoparticles, hydrogels, films, minirods and minipellets. There are over 30 therapeutic compounds that have been investigated with protein-based drug delivery platforms for the potential treatment of various cancers, infectious diseases, chronic diseases, autoimmune diseases. In protein-based drug delivery platforms, protein cage is the most newly developed biomaterials for drug delivery and therapeutic applications. Their uniform sizes, multifunctions, and biodegradability push them to the frontier for drug delivery. In this review, the recent strategic development of drug delivery has been discussed with a special emphasis upon the polymer based, especially protein-based nanomedicine platforms for drug delivery. The advantages and disadvantages are also discussed for each type of protein based drug delivery system.« less

Implementing drug abuse treatment services in criminal justice settings: Introduction to the CJ-DATS study protocol series.

PubMed

Ducharme, Lori J; Chandler, Redonna K; Wiley, Tisha R A

2013-12-01

Despite a growing pipeline of effective clinical treatments, there remains a persistent research-to-practice gap in drug abuse services. Delivery of effective treatment services is especially lacking in the U.S. criminal justice system, where half of all incarcerated persons meet the need for drug abuse or dependence, yet few receive needed care. Structural, financial, philosophical and other barriers slow the pace of adoption of available evidence-based practices. These challenges led to the development of a multi-site cooperative research endeavor known as the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS), funded by the National Institute on Drug Abuse (NIDA). CJ-DATS engages university-based research teams, criminal justice agencies, and community-based treatment providers in implementation research studies to test strategies for enhancing treatment service delivery to offender populations. This Introduction reviews the mission of NIDA, the structure and goals of the CJ-DATS cooperative, and the implementation studies being conducted by the participating organizations. The component Study Protocols in this article collection are then described. CJ-DATS applies implementation science perspectives and methods to address a vexing problem - the need to link offender populations with effective treatment for drug abuse, HIV, and other related conditions for which they are at high risk. Applying these principles to the U.S. criminal justice system is an innovative extension of lessons that have been learned in mainstream healthcare settings. This collection is offered as both an introduction to NIDA's work in this area, as well as a window onto the challenges of conducting health services research in settings in which improving public health is not the organization's core mission.

3D MI-DRAGON: new model for the reconstruction of US FDA drug- target network and theoretical-experimental studies of inhibitors of rasagiline derivatives for AChE.

PubMed

Prado-Prado, Francisco; García-Mera, Xerardo; Escobar, Manuel; Alonso, Nerea; Caamaño, Olga; Yañez, Matilde; González-Díaz, Humberto

2012-01-01

The number of neurodegenerative diseases has been increasing in recent years. Many of the drug candidates to be used in the treatment of neurodegenerative diseases present specific 3D structural features. An important protein in this sense is the acetylcholinesterase (AChE), which is the target of many Alzheimer's dementia drugs. Consequently, the prediction of Drug-Protein Interactions (DPIs/nDPIs) between new drug candidates and specific 3D structure and targets is of major importance. To this end, we can use Quantitative Structure-Activity Relationships (QSAR) models to carry out a rational DPIs prediction. Unfortunately, many previous QSAR models developed to predict DPIs take into consideration only 2D structural information and codify the activity against only one target. To solve this problem we can develop some 3D multi-target QSAR (3D mt-QSAR) models. In this study, using the 3D MI-DRAGON technique, we have introduced a new predictor for DPIs based on two different well-known software. We have used the MARCH-INSIDE (MI) and DRAGON software to calculate 3D structural parameters for drugs and targets respectively. Both classes of 3D parameters were used as input to train Artificial Neuronal Network (ANN) algorithms using as benchmark dataset the complex network (CN) made up of all DPIs between US FDA approved drugs and their targets. The entire dataset was downloaded from the DrugBank database. The best 3D mt-QSAR predictor found was an ANN of Multi-Layer Perceptron-type (MLP) with profile MLP 37:37-24-1:1. This MLP classifies correctly 274 out of 321 DPIs (Sensitivity = 85.35%) and 1041 out of 1190 nDPIs (Specificity = 87.48%), corresponding to training Accuracy = 87.03%. We have validated the model with external predicting series with Sensitivity = 84.16% (542/644 DPIs; Specificity = 87.51% (2039/2330 nDPIs) and Accuracy = 86.78%. The new CNs of DPIs reconstructed from US FDA can be used to explore large DPI databases in order to discover both new drugs and/or targets. We have carried out some theoretical-experimental studies to illustrate the practical use of 3D MI-DRAGON. First, we have reported the prediction and pharmacological assay of 22 different rasagiline derivatives with possible AChE inhibitory activity. In this work, we have reviewed different computational studies on Drug- Protein models. First, we have reviewed 10 studies on DP computational models. Next, we have reviewed 2D QSAR, 3D QSAR, CoMFA, CoMSIA and Docking with different compounds to find Drug-Protein QSAR models. Last, we have developped a 3D multi-target QSAR (3D mt-QSAR) models for the prediction of the activity of new compounds against different targets or the discovery of new targets.

Improving short antimicrobial peptides despite elusive rules for activity.

PubMed

Mikut, Ralf; Ruden, Serge; Reischl, Markus; Breitling, Frank; Volkmer, Rudolf; Hilpert, Kai

2016-05-01

Antimicrobial peptides (AMPs) can effectively kill a broad range of life threatening multidrug-resistant bacteria, a serious threat to public health worldwide. However, despite great hopes novel drugs based on AMPs are still rare. To accelerate drug development we studied different approaches to improve the antibacterial activity of short antimicrobial peptides. Short antimicrobial peptides seem to be ideal drug candidates since they can be synthesized quickly and easily, modified and optimized. In addition, manufacturing a short peptide drug will be more cost efficient than long and structured ones. In contrast to longer and structured peptides short AMPs seem hard to design and predict. Here, we designed, synthesized and screened five different peptide libraries, each consisting of 600 9-mer peptides, against Pseudomonas aeruginosa. Each library is presenting a different approach to investigate effectiveness of an optimization strategy. The data for the 3000 peptides were analyzed using models based on fuzzy logic bioinformatics and plausible descriptors. The rate of active or superior active peptides was improved from 31.0% in a semi-random library from a previous study to 97.8% in the best new designed library. This article is part of a Special Issue entitled: Antimicrobial peptides edited by Karl Lohner and Kai Hilpert. Copyright © 2015 Elsevier B.V. All rights reserved.

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials

PubMed Central

Federer, Callie; Yoo, Minjae

2016-01-01

Abstract Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov (https://clinicaltrials.gov/), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov. Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs. PMID:27631620

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

PubMed

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

Discovery of an ultra-short linear antibacterial tetrapeptide with anti-MRSA activity from a structure-activity relationship study.

PubMed

Lau, Qiu Ying; Ng, Fui Mee; Cheong, Jin Wei Darryl; Yap, Yi Yong Alvin; Tan, Yoke Yan Fion; Jureen, Roland; Hill, Jeffrey; Chia, Cheng San Brian

2015-11-13

The overuse and misuse of antibiotics has resulted in the emergence of drug-resistant pathogenic bacteria, including meticillin-resistant Staphylococcus aureus (MRSA), the primary pathogen responsible for human skin and soft-tissue infections. Antibacterial peptides are known to kill bacteria by rapidly disrupting their membranes and are deemed plausible alternatives to conventional antibiotics. One advantage of their membrane-targeting mode of action is that bacteria are unlikely to develop resistance as changing their cell membrane structure and morphology would likely involve extensive genetic mutations. However, major concerns in using peptides as antibacterial drugs include their instability towards plasma proteases, toxicity towards human cells due to their membrane-targeting mode of action and high manufacturing cost. These concerns can be mitigated by developing peptides as topical agents, by the judicial selection of amino acids and developing very short peptides respectively. In this preliminary report, we reveal a linear, non-hemolytic tetrapeptide with rapid bactericidal activity against MRSA developed from a structure-activity relationship study based on the antimicrobial hexapeptide WRWRWR-NH2. Our finding opens promising avenues for the development of ultra-short antibacterials to treat multidrug-resistant MRSA skin and soft tissue infections. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Microdroplet engineering for microbioassay and synthesis of functional structured porous particles

NASA Astrophysics Data System (ADS)

Rastogi, Vinayak

We present methods where sessile or suspended microdroplets are used to develop applications in the areas of bio-detection, photonics, drug delivery and catalysis. The first technique we report is for droplet-on-a-chip microbioassays. The assays are performed in droplet micro-containers suspended on the surface of high density fluorinated oil and are based on the process of agglutination of antibody-coated particles. Droplet microbioassays for the detection of Ricin were designed and their performance was compared to the standard handheld field assays. These droplet microbioassays were found to be 10 times more sensitive in terms of analyte concentration while requiring 100 times smaller volumes. We developed a model for the agglutination kinetics and mass transfer processes inside the droplets, which correlates well with the experimental data. The second technique that we developed uses droplet templates dispensed on superhydrophobic substrates for the fabrication of a new class of three dimensional hierarchical microsphere assemblies. The technique is termed Dry Self Assembly (DSA) since the fabricated supraparticles are easily detached from the substrate and collected unlike methods where assembled structures are suspended in liquid environment. The sessile droplet templates cast the final supraparticles into light diffracting near-spherical assemblies. When illuminated with a collimated beam of light, the structures exhibit unique ring shaped color diffraction patterns on their surface. The experimental observations for the angular position and wavelength corresponding to a spot on the rings are interpreted using a surface diffraction grating model. We also tailored the DSA method to produce both shape-anisotropic and composition-anisotropic supraparticles. The shape anisotropy was demonstrated by fabricating "doughnut" assemblies using droplets of both pure silica suspensions and silica mixed with gold nanoparticles. The composition anisotropy was realized by redistribution of magnetic nanoparticles in droplets containing mixtures of latex and magnetic particle suspensions. The redistribution is dictated by the pattern of magnetic field to which the droplet templates are introduced during drying. We developed new types of patchy magnetic particles that can find application in targeted drug delivery. The latex matrix can be infused with a drug and the magnetic patch(es) facilitate remote manipulation of the carrier. A new microfluidic chip was developed for the in-vitro characterization of drug/material release rate from the porous latex network in a live environment. The release rate of dye (drug simulant) from the porous supports is quantified and interpreted on the basis of diffusion/dissolution based mass transfer models. The technique has the potential to perform simultaneous screening of multiple samples and replace the conventional bulk laboratory setup needed for determining the release profiles in drug development process.

Novel Fluorescent Microemulsion: Probing Properties, Investigating Mechanism, and Unveiling Potential Application.

PubMed

Hou, Mengna; Dang, Leping; Liu, Tiankuo; Guo, Yun; Wang, Zhanzhong

2017-08-09

Nanoscale microemulsions have been utilized as delivery carriers for nutraceuticals and active biological drugs. Herein, we designed and synthesized a novel oil in water (O/W) fluorescent microemulsion based on isoamyl acetate, polyoxyethylene castor oil EL (CrEL), and water. The microemulsion emitted bright blue fluorescence, thus exhibiting its potential for active drug detection with label-free strategy. The microemulsion exhibited excitation-dependent emission and distinct red shift with longer excitation wavelengths. Lifetime and quantum yield of fluorescent microemulsion were 2.831 ns and 5.0%, respectively. An excellent fluorescent stability of the microemulsion was confirmed by altering pH, ionic strength, temperature, and time. Moreover, we proposed a probable mechanism of fluorochromic phenomenon, in connection with the aromatic ring structure of polyoxyethylene ether substituent in CrEL. Based on our findings, we concluded that this new fluorescent microemulsion is a promising drug carrier that can facilitate active drug detection with a label-free strategy. Although further research is required to understand the exact mechanism behind its fluorescence property, this work provided valuable guidance to develop new biosensors based on fluorescent microemulsion.

MoFvAb: Modeling the Fv region of antibodies

PubMed Central

Bujotzek, Alexander; Fuchs, Angelika; Qu, Changtao; Benz, Jörg; Klostermann, Stefan; Antes, Iris; Georges, Guy

2015-01-01

Knowledge of the 3-dimensional structure of the antigen-binding region of antibodies enables numerous useful applications regarding the design and development of antibody-based drugs. We present a knowledge-based antibody structure prediction methodology that incorporates concepts that have arisen from an applied antibody engineering environment. The protocol exploits the rich and continuously growing supply of experimentally derived antibody structures available to predict CDR loop conformations and the packing of heavy and light chain quickly and without user intervention. The homology models are refined by a novel antibody-specific approach to adapt and rearrange sidechains based on their chemical environment. The method achieves very competitive all-atom root mean square deviation values in the order of 1.5 Å on different evaluation datasets consisting of both known and previously unpublished antibody crystal structures. PMID:26176812

Development of new drugs for an old target: the penicillin binding proteins.

PubMed

Zervosen, Astrid; Sauvage, Eric; Frère, Jean-Marie; Charlier, Paulette; Luxen, André

2012-10-24

The widespread use of β-lactam antibiotics has led to the worldwide appearance of drug-resistant strains. Bacteria have developed resistance to β-lactams by two main mechanisms: the production of β-lactamases, sometimes accompanied by a decrease of outer membrane permeability, and the production of low-affinity, drug resistant Penicillin Binding Proteins (PBPs). PBPs remain attractive targets for developing new antibiotic agents because they catalyse the last steps of the biosynthesis of peptidoglycan, which is unique to bacteria, and lies outside the cytoplasmic membrane. Here we summarize the “current state of the art” of non-β-lactam inhibitors of PBPs, which have being developed in an attempt to counter the emergence of β-lactam resistance. These molecules are not susceptible to hydrolysis by β-lactamases and thus present a real alternative to β-lactams. We present transition state analogs such as boronic acids, which can covalently bind to the active serine residue in the catalytic site. Molecules containing ring structures different from the β-lactam-ring like lactivicin are able to acylate the active serine residue. High throughput screening methods, in combination with virtual screening methods and structure based design, have allowed the development of new molecules. Some of these novel inhibitors are active against major pathogens, including methicillin-resistant Staphylococcus aureus (MRSA) and thus open avenues new for the discovery of novel antibiotics.

Categorizing Drugs and Drug-Taking: A More Meaningful Approach.

ERIC Educational Resources Information Center

Gold, Robert S.; Duncan, David F.

This document reviews various definitions of the nature and classification of drugs. Difficulties with existing categorizations which use such bases as clinical utility, molecular structure, effects on the central nervous system, legality, and hazard potential are disucssed. A more meaningful categorization based on the availability and sources of…

ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

PubMed

González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

2014-03-24

This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

Virtual High-Throughput Screening for Matrix Metalloproteinase Inhibitors.

PubMed

Choi, Jun Yong; Fuerst, Rita

2017-01-01

Structure-based virtual screening (SBVS) is a common method for the fast identification of hit structures at the beginning of a medicinal chemistry program in drug discovery. The SBVS, described in this manuscript, is focused on finding small molecule hits that can be further utilized as a starting point for the development of inhibitors of matrix metalloproteinase 13 (MMP-13) via structure-based molecular design. We intended to identify a set of structurally diverse hits, which occupy all subsites (S1'-S3', S2, and S3) centering the zinc containing binding site of MMP-13, by the virtual screening of a chemical library comprising more than ten million commercially available compounds. In total, 23 compounds were found as potential MMP-13 inhibitors using Glide docking followed by the analysis of the structural interaction fingerprints (SIFt) of the docked structures.

Optimization of the qualitative composition of liposomal drugs based on natural organomineral formations

NASA Astrophysics Data System (ADS)

Chzhu, O. P.; Shubenkova, E. G.

2017-08-01

Liposomal structures were developed on the basis of oil and water extracts of natural organomineral formations. These structures are natural compositions. The content of the main components in the preparations varies within the range of 20-25% of the lipophilic phase, 64-74% of the hydrophilic phase, 5-10% of the auxiliary component and the stabilizer on the phospholipid base is 1%. Phospholipids of natural origin were used as surface-active substances. The influence of hydrophilic and lipophilic auxiliary components on the content of neutral lipids in the surface lipid layer of the skin was studied. The developed preparations can be used as carriers of both hydrophilic and lipophilic active substances in pharmaceutical compositions, cosmetic and veterinary products on a natural basis.

CancerHSP: anticancer herbs database of systems pharmacology

NASA Astrophysics Data System (ADS)

Tao, Weiyang; Li, Bohui; Gao, Shuo; Bai, Yaofei; Shar, Piar Ali; Zhang, Wenjuan; Guo, Zihu; Sun, Ke; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Mu, Jiexin; Pei, Tianli; Wang, Yuan; Li, Yan; Wang, Yonghua

2015-06-01

The numerous natural products and their bioactivity potentially afford an extraordinary resource for new drug discovery and have been employed in cancer treatment. However, the underlying pharmacological mechanisms of most natural anticancer compounds remain elusive, which has become one of the major obstacles in developing novel effective anticancer agents. Here, to address these unmet needs, we developed an anticancer herbs database of systems pharmacology (CancerHSP), which records anticancer herbs related information through manual curation. Currently, CancerHSP contains 2439 anticancer herbal medicines with 3575 anticancer ingredients. For each ingredient, the molecular structure and nine key ADME parameters are provided. Moreover, we also provide the anticancer activities of these compounds based on 492 different cancer cell lines. Further, the protein targets of the compounds are predicted by state-of-art methods or collected from literatures. CancerHSP will help reveal the molecular mechanisms of natural anticancer products and accelerate anticancer drug development, especially facilitate future investigations on drug repositioning and drug discovery. CancerHSP is freely available on the web at http://lsp.nwsuaf.edu.cn/CancerHSP.php.

The shikimate pathway: review of amino acid sequence, function and three-dimensional structures of the enzymes.

PubMed

Mir, Rafia; Jallu, Shais; Singh, T P

2015-06-01

The aromatic compounds such as aromatic amino acids, vitamin K and ubiquinone are important prerequisites for the metabolism of an organism. All organisms can synthesize these aromatic metabolites through shikimate pathway, except for mammals which are dependent on their diet for these compounds. The pathway converts phosphoenolpyruvate and erythrose 4-phosphate to chorismate through seven enzymatically catalyzed steps and chorismate serves as a precursor for the synthesis of variety of aromatic compounds. These enzymes have shown to play a vital role for the viability of microorganisms and thus are suggested to present attractive molecular targets for the design of novel antimicrobial drugs. This review focuses on the seven enzymes of the shikimate pathway, highlighting their primary sequences, functions and three-dimensional structures. The understanding of their active site amino acid maps, functions and three-dimensional structures will provide a framework on which the rational design of antimicrobial drugs would be based. Comparing the full length amino acid sequences and the X-ray crystal structures of these enzymes from bacteria, fungi and plant sources would contribute in designing a specific drug and/or in developing broad-spectrum compounds with efficacy against a variety of pathogens.

Development of biodegradable polymer based tamoxifen citrate loaded nanoparticles and effect of some manufacturing process parameters on them: a physicochemical and in-vitro evaluation.

PubMed

Sahana, Basudev; Santra, Kousik; Basu, Sumit; Mukherjee, Biswajit

2010-09-07

The aim of the present study was to develop nanoparticles of tamoxifen citrate, a non-steroidal antiestrogenic drug used for the treatment of breast cancer. Biodegradable poly (D, L- lactide-co-glycolide)-85:15 (PLGA) was used to develop nanoparticles of tamoxifen citrate by multiple emulsification (w/o/w) and solvent evaporation technique. Drug-polymer ratio, polyvinyl alcohol concentrations, and homogenizing speeds were varied at different stages of preparation to optimize the desired size and release profile of drug. The characterization of particle morphology and shape was performed by field emission scanning electron microscope (FE-SEM) and particle size distribution patterns were studied by direct light scattering method using zeta sizer. In vitro drug release study showed that release profile of tamoxifen from biodegradable nanoparticles varied due to the change in speed of centrifugation for separation. Drug loading efficiency varied from 18.60% to 71.98%. The FE-SEM study showed that biodegradable nanoparticles were smooth and spherical in shape. The stability studies of tamoxifen citrate in the experimental nanoparticles showed the structural integrity of tamoxifen citrate in PLGA nanoparticles up to 60°C in the tested temperatures. Nanoparticles containing tamoxifen citrate could be useful for the controlled delivery of the drug for a prolonged period.

Application of 3D-QSAR in the rational design of receptor ligands and enzyme inhibitors.

PubMed

Mor, Marco; Rivara, Silvia; Lodola, Alessio; Lorenzi, Simone; Bordi, Fabrizio; Plazzi, Pier Vincenzo; Spadoni, Gilberto; Bedini, Annalida; Duranti, Andrea; Tontini, Andrea; Tarzia, Giorgio

2005-11-01

Quantitative structure-activity relationships (QSARs) are frequently employed in medicinal chemistry projects, both to rationalize structure-activity relationships (SAR) for known series of compounds and to help in the design of innovative structures endowed with desired pharmacological actions. As a difference from the so-called structure-based drug design tools, they do not require the knowledge of the biological target structure, but are based on the comparison of drug structural features, thus being defined ligand-based drug design tools. In the 3D-QSAR approach, structural descriptors are calculated from molecular models of the ligands, as interaction fields within a three-dimensional (3D) lattice of points surrounding the ligand structure. These descriptors are collected in a large X matrix, which is submitted to multivariate analysis to look for correlations with biological activity. Like for other QSARs, the reliability and usefulness of the correlation models depends on the validity of the assumptions and on the quality of the data. A careful selection of compounds and pharmacological data can improve the application of 3D-QSAR analysis in drug design. Some examples of the application of CoMFA and CoMSIA approaches to the SAR study and design of receptor or enzyme ligands is described, pointing the attention to the fields of melatonin receptor ligands and FAAH inhibitors.

Homology modeling a fast tool for drug discovery: current perspectives.

PubMed

Vyas, V K; Ukawala, R D; Ghate, M; Chintha, C

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives

PubMed Central

Vyas, V. K.; Ukawala, R. D.; Ghate, M.; Chintha, C.

2012-01-01

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery. PMID:23204616

Utilizing Structures of CYP2D6 and BACE1 Complexes To Reduce Risk of Drug–Drug Interactions with a Novel Series of Centrally Efficacious BACE1 Inhibitors

PubMed Central

2016-01-01

In recent years, the first generation of β-secretase (BACE1) inhibitors advanced into clinical development for the treatment of Alzheimer’s disease (AD). However, the alignment of drug-like properties and selectivity remains a major challenge. Herein, we describe the discovery of a novel class of potent, low clearance, CNS penetrant BACE1 inhibitors represented by thioamidine 5. Further profiling suggested that a high fraction of the metabolism (>95%) was due to CYP2D6, increasing the potential risk for victim-based drug–drug interactions (DDI) and variable exposure in the clinic due to the polymorphic nature of this enzyme. To guide future design, we solved crystal structures of CYP2D6 complexes with substrate 5 and its corresponding metabolic product pyrazole 6, which provided insight into the binding mode and movements between substrate/inhibitor complexes. Guided by the BACE1 and CYP2D6 crystal structures, we designed and synthesized analogues with reduced risk for DDI, central efficacy, and improved hERG therapeutic margins. PMID:25781223

Thiolated alginate-based multiple layer mucoadhesive films of metformin forintra-pocket local delivery: in vitro characterization and clinical assessment.

PubMed

Kassem, Abeer Ahmed; Issa, Doaa Ahmed Elsayed; Kotry, Gehan Sherif; Farid, Ragwa Mohamed

2017-01-01

Periodontal disease broadly defines group of conditions in which the supportive structure of the tooth (periodontium) is destroyed. Recent studies suggested that the anti-diabetic drug metformin hydrochloride (MF) has an osteogenic effect and is beneficial for the management of periodontitis. Development of strong mucoadhesive multiple layer film loading small dose of MF for intra-pocket application. Multiple layer film was developed by double casting followed by compression method. Either 6% carboxy methyl cellulose sodium (CMC) or sodium alginate (ALG) constituted the inner drug (0.6%) loaded layer. Thiolated sodium alginate (TSA; 2 or 4%) constituted the outer drug free layers to enhance mucoadhesion and achieve controlled drug release. Optimized formulation was assessed clinically on 20 subjects. Films were uniform, thin and hard enough for easy insertion into periodontal pockets. Based on water uptake and in vitro drug release, CMC based film with 4% TSA as an outer layer was the optimized formulation with enhanced mucoadhesion and controlled drug release (83.73% over 12 h). SEM showed the effective fabrication of the triple layer film in which connective lines between the layers could be observed. FTIR examination suggests possibility of hydrogen bonding between the -NH groups of metformin and -OH groups of CMC. DSC revealed the presence of MF mainly in the amorphous form. Clinical results indicated improvement of all clinical parameters six months post treatment. The results suggested that local application of the mucoadhesive multiple layer films loaded with metformin hydrochloride was able to manage moderate chronic periodontitis.

Integrating High-Dimensional Transcriptomics and Image Analysis Tools into Early Safety Screening: Proof of Concept for a New Early Drug Development Strategy.

PubMed

Verbist, Bie M P; Verheyen, Geert R; Vervoort, Liesbet; Crabbe, Marjolein; Beerens, Dominiek; Bosmans, Cindy; Jaensch, Steffen; Osselaer, Steven; Talloen, Willem; Van den Wyngaert, Ilse; Van Hecke, Geert; Wuyts, Dirk; Van Goethem, Freddy; Göhlmann, Hinrich W H

2015-10-19

During drug discovery and development, the early identification of adverse effects is expected to reduce costly late-stage failures of candidate drugs. As risk/safety assessment takes place rather late during the development process and due to the limited ability of animal models to predict the human situation, modern unbiased high-dimensional biology readouts are sought, such as molecular signatures predictive for in vivo response using high-throughput cell-based assays. In this theoretical proof of concept, we provide findings of an in-depth exploration of a single chemical core structure. Via transcriptional profiling, we identified a subset of close analogues that commonly downregulate multiple tubulin genes across cellular contexts, suggesting possible spindle poison effects. Confirmation via a qualified toxicity assay (in vitro micronucleus test) and the identification of a characteristic aggregate-formation phenotype via exploratory high-content imaging validated the initial findings. SAR analysis triggered the synthesis of a new set of compounds and allowed us to extend the series showing the genotoxic effect. We demonstrate the potential to flag toxicity issues by utilizing data from exploratory experiments that are typically generated for target evaluation purposes during early drug discovery. We share our thoughts on how this approach may be incorporated into drug development strategies.

The application of a novel high-resolution mass spectrometry-based analytical strategy to rapid metabolite profiling of a dual drug combination in humans.

PubMed

Xing, Jie; Zang, Meitong; Liu, Huixiang

2017-11-15

Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension. First, mass defect filter (MDF), as a targeted data mining tool, worked effectively except for those metabolites with similar MDF values. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, was able to recover all relevant metabolites of VER-IRB from the full-scan MS dataset except for trace metabolites buried in the background noise and/or combined drug-related signals. Third, the novel ring double bond (RDB; valence values of elements in structure) filter, could show rich structural information in more sensitive full-scan MS chromatograms; however, it had a low capability to remove background noise and was difficult to differentiate the metabolites with RDB coverage. Fourth, an integrated strategy, i.e., untargeted BS followed by RDB, was effective for metabolite identification of VER and IRB, which have different RDB values. Majority of matrix signals were firstly removed using BS. Metabolite ions for each parent drug were then isolated from remaining background matrix and combined drug-related signals by imposing of preset RDB values/ranges around the parent drug and selected core substructures. In parallel, MDF was used to recover potential metabolites with similar RDB. As a result, a total of 74 metabolites were found for VER-IRB in human plasma and urine, among which ten metabolites have not been previously reported in human. The results demonstrated that the combination of accurate mass-based multiple data-mining techniques, i.e., untargeted background subtraction followed by ring double bond filtering in parallel with targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drug. Copyright © 2017 Elsevier B.V. All rights reserved.

A Review of the Structure, Preparation, and Application of NLCs, PNPs, and PLNs.

PubMed

Li, Qianwen; Cai, Tiange; Huang, Yinghong; Xia, Xi; Cole, Susan P C; Cai, Yu

2017-05-27

Nanostructured lipid carriers (NLCs) are modified solid lipid nanoparticles (SLNs) that retain the characteristics of the SLN, improve drug stability and loading capacity, and prevent drug leakage. Polymer nanoparticles (PNPs) are an important component of drug delivery. These nanoparticles can effectively direct drug delivery to specific targets and improve drug stability and controlled drug release. Lipid-polymer nanoparticles (PLNs), a new type of carrier that combines liposomes and polymers, have been employed in recent years. These nanoparticles possess the complementary advantages of PNPs and liposomes. A PLN is composed of a core-shell structure; the polymer core provides a stable structure, and the phospholipid shell offers good biocompatibility. As such, the two components increase the drug encapsulation efficiency rate, facilitate surface modification, and prevent leakage of water-soluble drugs. Hence, we have reviewed the current state of development for the NLCs', PNPs', and PLNs' structures, preparation, and applications over the past five years, to provide the basis for further study on a controlled release drug delivery system.

A Review of the Structure, Preparation, and Application of NLCs, PNPs, and PLNs

PubMed Central

Li, Qianwen; Cai, Tiange; Huang, Yinghong; Xia, Xi; Cole, Susan P. C.; Cai, Yu

2017-01-01

Nanostructured lipid carriers (NLCs) are modified solid lipid nanoparticles (SLNs) that retain the characteristics of the SLN, improve drug stability and loading capacity, and prevent drug leakage. Polymer nanoparticles (PNPs) are an important component of drug delivery. These nanoparticles can effectively direct drug delivery to specific targets and improve drug stability and controlled drug release. Lipid–polymer nanoparticles (PLNs), a new type of carrier that combines liposomes and polymers, have been employed in recent years. These nanoparticles possess the complementary advantages of PNPs and liposomes. A PLN is composed of a core–shell structure; the polymer core provides a stable structure, and the phospholipid shell offers good biocompatibility. As such, the two components increase the drug encapsulation efficiency rate, facilitate surface modification, and prevent leakage of water-soluble drugs. Hence, we have reviewed the current state of development for the NLCs’, PNPs’, and PLNs’ structures, preparation, and applications over the past five years, to provide the basis for further study on a controlled release drug delivery system. PMID:28554993

Nanotechnology-based drug delivery systems for control of microbial biofilms: a review.

PubMed

Dos Santos Ramos, Matheus Aparecido; Da Silva, Patrícia Bento; Spósito, Larissa; De Toledo, Luciani Gaspar; Bonifácio, Bruna Vidal; Rodero, Camila Fernanda; Dos Santos, Karen Cristina; Chorilli, Marlus; Bauab, Taís Maria

2018-01-01

Since the dawn of civilization, it has been understood that pathogenic microorganisms cause infectious conditions in humans, which at times, may prove fatal. Among the different virulent properties of microorganisms is their ability to form biofilms, which has been directly related to the development of chronic infections with increased disease severity. A problem in the elimination of such complex structures (biofilms) is resistance to the drugs that are currently used in clinical practice, and therefore, it becomes imperative to search for new compounds that have anti-biofilm activity. In this context, nanotechnology provides secure platforms for targeted delivery of drugs to treat numerous microbial infections that are caused by biofilms. Among the many applications of such nanotechnology-based drug delivery systems is their ability to enhance the bioactive potential of therapeutic agents. The present study reports the use of important nanoparticles, such as liposomes, microemulsions, cyclodextrins, solid lipid nanoparticles, polymeric nanoparticles, and metallic nanoparticles, in controlling microbial biofilms by targeted drug delivery. Such utilization of these nanosystems has led to a better understanding of their applications and their role in combating biofilms.

Nanotechnology-based drug delivery systems for control of microbial biofilms: a review

PubMed Central

Dos Santos Ramos, Matheus Aparecido; Da Silva, Patrícia Bento; Spósito, Larissa; De Toledo, Luciani Gaspar; Bonifácio, Bruna Vidal; Rodero, Camila Fernanda; Dos Santos, Karen Cristina; Chorilli, Marlus; Bauab, Taís Maria

2018-01-01

Since the dawn of civilization, it has been understood that pathogenic microorganisms cause infectious conditions in humans, which at times, may prove fatal. Among the different virulent properties of microorganisms is their ability to form biofilms, which has been directly related to the development of chronic infections with increased disease severity. A problem in the elimination of such complex structures (biofilms) is resistance to the drugs that are currently used in clinical practice, and therefore, it becomes imperative to search for new compounds that have anti-biofilm activity. In this context, nanotechnology provides secure platforms for targeted delivery of drugs to treat numerous microbial infections that are caused by biofilms. Among the many applications of such nanotechnology-based drug delivery systems is their ability to enhance the bioactive potential of therapeutic agents. The present study reports the use of important nanoparticles, such as liposomes, microemulsions, cyclodextrins, solid lipid nanoparticles, polymeric nanoparticles, and metallic nanoparticles, in controlling microbial biofilms by targeted drug delivery. Such utilization of these nanosystems has led to a better understanding of their applications and their role in combating biofilms. PMID:29520143

Silk Electrogel Based Gastroretentive Drug Delivery System

NASA Astrophysics Data System (ADS)

Wang, Qianrui

Gastric cancer has become a global pandemic and there is imperative to develop efficient therapies. Oral dosing strategy is the preferred route to deliver drugs for treating the disease. Recent studies suggested silk electro hydrogel, which is pH sensitive and reversible, has potential as a vehicle to deliver the drug in the stomach environment. The aim of this study is to establish in vitro electrogelation e-gel based silk gel as a gastroretentive drug delivery system. We successfully extended the duration of silk e-gel in artificial gastric juice by mixing silk solution with glycerol at different ratios before the electrogelation. Structural analysis indicated the extended duration was due to the change of beta sheet content. The glycerol mixed silk e-gel had good doxorubicin loading capability and could release doxorubicin in a sustained-release profile. Doxorubicin loaded silk e-gels were applied to human gastric cancer cells. Significant cell viability decrease was observed. We believe that with further characterization as well as functional analysis, the silk e-gel system has the potential to become an effective vehicle for gastric drug delivery applications.

Impact of data base structure in a successful in vitro-in vivo correlation for pharmaceutical products.

PubMed

Roudier, B; Davit, B; Schütz, H; Cardot, J-M

2015-01-01

The in vitro-in vivo correlation (IVIVC) (Food and Drug Administration 1997) aims to predict performances in vivo of a pharmaceutical formulation based on its in vitro characteristics. It is a complex process that (i) incorporates in a gradual and incremental way a large amount of information and (ii) requires information from different properties (formulation, analytical, clinical) and associated dedicated treatments (statistics, modeling, simulation). These results in many studies that are initiated and integrated into the specifications (quality target product profile, QTPP). This latter defines the appropriate experimental designs (quality by design, QbD) (Food and Drug Administration 2011, 2012) whose main objectives are determination (i) of key factors of development and manufacturing (critical process parameters, CPPs) and (ii) of critical points of physicochemical nature relating to active ingredients (API) and critical quality attribute (CQA) which may have implications in terms of efficiency, safety, and inoffensiveness for the patient, due to their non-inclusion. These processes generate a very large amount of data that is necessary to structure. In this context, the storage of information in a database (DB) and the management of this database (database management system, DBMS) become an important issue for the management of projects and IVIVC and more generally for development of new pharmaceutical forms. This article describes the implementation of a prototype object-oriented database (OODB) considered as a tool, which is helpful for decision taking, responding in a structured and consistent way to the issues of project management of IVIVC (including bioequivalence and bioavailability) (Food and Drug Administration 2003) necessary for the implementation of QTPP.

Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library.

PubMed

Shah, Falgun; Mukherjee, Prasenjit; Gut, Jiri; Legac, Jennifer; Rosenthal, Philip J; Tekwani, Babu L; Avery, Mitchell A

2011-04-25

Malaria, in particular that caused by Plasmodium falciparum , is prevalent across the tropics, and its medicinal control is limited by widespread drug resistance. Cysteine proteases of P. falciparum , falcipain-2 (FP-2) and falcipain-3 (FP-3), are major hemoglobinases, validated as potential antimalarial drug targets. Structure-based virtual screening of a focused cysteine protease inhibitor library built with soft rather than hard electrophiles was performed against an X-ray crystal structure of FP-2 using the Glide docking program. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FP-2 from a large chemical database. Biological evaluation of 50 selected compounds identified 21 diverse nonpeptidic inhibitors of FP-2 with a hit rate of 42%. Atomic Fukui indices were used to predict the most electrophilic center and its electrophilicity in the identified hits. Comparison of predicted electrophilicity of electrophiles in identified hits with those in known irreversible inhibitors suggested the soft-nature of electrophiles in the selected target compounds. The present study highlights the importance of focused libraries and enrichment studies in structure-based virtual screening. In addition, few compounds were screened against homologous human cysteine proteases for selectivity analysis. Further evaluation of structure-activity relationships around these nonpeptidic scaffolds could help in the development of selective leads for antimalarial chemotherapy.

Dendrimers: a class of polymers in the nanotechnology for the delivery of active pharmaceuticals.

PubMed

Samad, Abdus; Alam, Md Intakhab; Saxena, Kinshuk

2009-01-01

Dendrimers represent a class of novel polymers having unique molecular architectures characterized by their well-defined structure, with a high degree of molecular uniformity, low polydispersity and properties that make them attractive materials for the development of nanomedicines. The dendrimer drug delivery can be achieved by coupling a drug through one of two approaches. Hydrophobic drugs can be complexed within the hydrophobic dendrimer interior to make them water-soluble or drugs can be covalently coupled onto the surface of the dendrimer. In addition, dendrimers have been shown to be capable of bypassing efflux transporters. A new generation of dendrimer-based delivery systems will enable the efficient transport of drugs across cellular barriers. This review deals principally with the synthesis, characterization and recent applications of dendrimers. In future it will only ever be possible to designate a dendrimer as safe means of drug delivery related to a specific application. However, so far limited clinical experience using dendrimers makes it impossible to designate any particular system which is safe and non toxic. Although there is widespread concern as to the safety of nanosized particles, preclinical and clinical experience gained during the development of polymeric excipients, biomedical polymers and polymer therapeutics showed that judicious development of dendrimer chemistry for each specific application will ensure development of safe and important materials for biomedical and pharmaceutical use.

Strategic incorporation of fluorine in the drug discovery of new-generation antitubercular agents targeting bacterial cell division protein FtsZ⋆

PubMed Central

Ojima, Iwao; Awasthi, Divya; Wei, Longfei; Haranahalli, Krupanandan

2016-01-01

This article presents an account of our research on the discovery and development of new-generation fluorine-containing antibacterial agents against drug-resistant tuberculosis, targeting FtsZ. FtsZ is an essential protein for bacterial cell division and a highly promising therapeutic target for antibacterial drug discovery. Through design, synthesis and semi-HTP screening of libraries of novel benzimidazoles, followed by SAR studies, we identified highly potent lead compounds. However, these lead compounds were found to lack sufficient metabolic and plasma stabilities. Accordingly, we have performed extensive study on the strategic incorporation of fluorine into lead compounds to improve pharmacological properties. This study has led to the development of highly efficacious fluorine-containing benzimidazoles as potential drug candidates. We have also performed computational docking analysis of these novel FtsZ inhibitors to identify their putative binding site. Based on the structural data and docking analysis, a plausible mode-of-action for this novel class of FtsZ inhibitors is proposed. PMID:28555087

Toxins and derivatives in molecular pharmaceutics: Drug delivery and targeted therapy.

PubMed

Zhan, Changyou; Li, Chong; Wei, Xiaoli; Lu, Wuyuan; Lu, Weiyue

2015-08-01

Protein and peptide toxins offer an invaluable source for the development of actively targeted drug delivery systems. They avidly bind to a variety of cognate receptors, some of which are expressed or even up-regulated in diseased tissues and biological barriers. Protein and peptide toxins or their derivatives can act as ligands to facilitate tissue- or organ-specific accumulation of therapeutics. Some toxins have evolved from a relatively small number of structural frameworks that are particularly suitable for addressing the crucial issues of potency and stability, making them an instrumental source of leads and templates for targeted therapy. The focus of this review is on protein and peptide toxins for the development of targeted drug delivery systems and molecular therapies. We summarize disease- and biological barrier-related toxin receptors, as well as targeted drug delivery strategies inspired by those receptors. The design of new therapeutics based on protein and peptide toxins is also discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparison of the pattern, efficacy, and tolerability of self-medicated drugs in primary dysmenorrhea: a questionnaire based survey.

PubMed

Sugumar, Ramya; Krishnaiah, Vasundara; Channaveera, Gokul Shetty; Mruthyunjaya, Shilpa

2013-01-01

To compare the pattern, efficacy, and tolerability of self-medicated drugs and to assess the adequacy of their dose in primary dysmenorrhea (PD). A survey using a self-developed, validated, objective, and structured questionnaire as a tool was conducted among subjects with PD. Statistical analysis was carried out using Chi-square test and ANOVA with post-hoc Tuckey's test. Out of 641 respondents, 42% were self-medicated. The pattern of drugs used was: Dicyclomine, an unknown drug, mefenamic acid, mefenamic acid + dicyclomine, and metamizole by 35%, 29%, 26%, 9%, and 1% of respondents, respectively. Mefenamic acid + dicyclomine, the combination was the most efficacious in comparison to other drugs in moderate to severe dysmenorrhea. There was better tolerability with mefenamic acid + dicyclomine group compared to other drugs. Sub-therapeutic doses were used by 86% of self-medicating respondents. The prevailing self-medication practices were inappropriate in a substantial proportion of women with inadequate knowledge regarding appropriate drug choice, therapeutic doses, and their associated side effects.

21 CFR 510.3 - Definitions and interpretations.

Code of Federal Regulations, 2011 CFR

2011-04-01

..., mitigating, treating, or preventing a disease, or to affect a structure or function of the animal body, even though such drug is not a new animal drug when used in another disease or to affect another structure or... drug as defined in part 516 of this chapter, who must be the real party in interest of the development...

21 CFR 510.3 - Definitions and interpretations.

Code of Federal Regulations, 2013 CFR

2013-04-01

..., mitigating, treating, or preventing a disease, or to affect a structure or function of the animal body, even though such drug is not a new animal drug when used in another disease or to affect another structure or... drug as defined in part 516 of this chapter, who must be the real party in interest of the development...

GPCR-SSFE 2.0-a fragment-based molecular modeling web tool for Class A G-protein coupled receptors.

PubMed

Worth, Catherine L; Kreuchwig, Franziska; Tiemann, Johanna K S; Kreuchwig, Annika; Ritschel, Michele; Kleinau, Gunnar; Hildebrand, Peter W; Krause, Gerd

2017-07-03

G-protein coupled receptors (GPCRs) are key players in signal transduction and therefore a large proportion of pharmaceutical drugs target these receptors. Structural data of GPCRs are sparse yet important for elucidating the molecular basis of GPCR-related diseases and for performing structure-based drug design. To ameliorate this problem, GPCR-SSFE 2.0 (http://www.ssfa-7tmr.de/ssfe2/), an intuitive web server dedicated to providing three-dimensional Class A GPCR homology models has been developed. The updated web server includes 27 inactive template structures and incorporates various new functionalities. Uniquely, it uses a fingerprint correlation scoring strategy for identifying the optimal templates, which we demonstrate captures structural features that sequence similarity alone is unable to do. Template selection is carried out separately for each helix, allowing both single-template models and fragment-based models to be built. Additionally, GPCR-SSFE 2.0 stores a comprehensive set of pre-calculated and downloadable homology models and also incorporates interactive loop modeling using the tool SL2, allowing knowledge-based input by the user to guide the selection process. For visual analysis, the NGL viewer is embedded into the result pages. Finally, blind-testing using two recently published structures shows that GPCR-SSFE 2.0 performs comparably or better than other state-of-the art GPCR modeling web servers. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Structural interpretation of P2X receptor mutagenesis studies on drug action.

PubMed

Evans, Richard J

2010-11-01

P2X receptors for ATP are ligand gated cation channels that form from the trimeric assembly of subunits with two transmembrane segments, a large extracellular ligand binding loop, and intracellular amino and carboxy termini. The receptors are expressed throughout the body, involved in functions ranging from blood clotting to inflammation, and may provide important targets for novel therapeutics. Mutagenesis based studies have been used to develop an understanding of the molecular basis of their pharmacology with the aim of developing models of the ligand binding site. A crystal structure for the zebra fish P2X4 receptor in the closed agonist unbound state has been published recently, which provides a major advance in our understanding of the receptors. This review gives an overview of mutagenesis studies that have led to the development of a model of the ATP binding site, as well as identifying residues contributing to allosteric regulation and antagonism. These studies are discussed with reference to the crystal to provide a structural interpretation of the molecular basis of drug action. © 2010 The Author. British Journal of Pharmacology © 2010 The British Pharmacological Society.

Amino acid–based surfactants: New antimicrobial agents.

PubMed

Pinazo, A; Manresa, M A; Marques, A M; Bustelo, M; Espuny, M J; Pérez, L

2016-02-01

The rapid increase of drug resistant bacteria makes necessary the development of new antimicrobial agents. Synthetic amino acid-based surfactants constitute a promising alternative to conventional antimicrobial compounds given that they can be prepared from renewable raw materials. In this review, we discuss the structural features that promote antimicrobial activity of amino acid-based surfactants. Monocatenary, dicatenary and gemini surfactants that contain different amino acids on the polar head and show activity against bacteria are revised. The synthesis and basic physico-chemical properties have also been included.

1,8-Naphthalimide: A Potent DNA Intercalator and Target for Cancer Therapy.

PubMed

Tandon, Runjhun; Luxami, Vijay; Kaur, Harsovin; Tandon, Nitin; Paul, Kamaldeep

2017-10-01

The poor pharmacokinetics, side effects and particularly the rapid emergence of drug resistance compromise the efficiency of clinically used anticancer drugs. Therefore, the discovery of novel and effective drugs is still an extremely primary mission. Naphthalimide family is one of the highly active anticancer drug based upon effective intercalator with DNA. In this article, we review the discovery and development of 1,8-naphthalimide moiety, and, especially, pay much attention to the structural modifications and structure activity relationships. The review demonstrates how modulation of the moiety affecting naphthalimide compound for DNA binding that is achieved to afford a profile of antitumor activity. The DNA binding of imide and ring substitution at naphthalimide, bisnaphthalimide, naphthalimide-metal complexes is achieved by molecular recognition through intercalation mode. Thus, this synthetic/natural small molecule can act as a drug when activation or inhibition of DNA function, is required to cure or control the cancer disease. The present study is a review of the advances in 1,8-naphthalimide-related research, with a focus on how such derivatives are intercalated into DNA for their anticancer activities. © 2017 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent Advances in Nanoparticle-Based Targeted Drug-Delivery Systems Against Cancer and Role of Tumor Microenvironment.

PubMed

Ashfaq, Usman Ali; Riaz, Muhammad; Yasmeen, Erum; Yousaf, Muhammad Zubair

2017-01-01

Cancer is one of the major causes of death worldwide. The silent activation of cellular factors responsible for deviation from normal regulatory pathways leads to the development of cancer. Nano-biotechnology is a novel drug-delivery system with high potential of efficacy and accuracy to target lethal cancers. Various biocompatible nanoparticle (NP)-based drug-delivery systems such as liposomes, dendrimers, micelles, silica, quantum dots, and magnetic, gold, and carbon nanotubes have already been reported for successful targeted cancer treatment. NPs are functionalized with different biological molecules, peptides, antibody, and protein ligands for targeted drug delivery. These systems include a hydrophilic central core, a target-oriented biocompatible outer layer, and a middle hydrophobic core where the drug destined to reach target site resides. Most of the NPs have the ability to maintain their structural shape and are constructed according to the cancer microenvironment. The self-assembling and colloidal properties of NPs have caused them to become the best vehicles for targeted drug delivery. The tumor microenvironment (TME) plays a major role in cancer progression, detection, and treatment. Due to its continuous complex behavior, the TME can hinder delivery systems, thus halting cancer treatment. Nonetheless, a successful biophysiological interaction between the NPs and the TME results in targeted release of drugs. Currently, a number of drugs and NP-based delivery systems against cancer are in clinical and preclinical trials and a few have been approved by Food and Drug Administration (FDA); for example: taxol, doxil, cerubidine, and adrucil. This review summarizes topical advances about the drugs being used for cancer treatment, their targeted delivery systems based on NPs, and the role of TME in this connection.