Target-based Approaches Research Articles

Accurate laser scanner to camera calibration with application to range sensor evaluation

Multi-modal sensory data plays an important role in many computer vision and robotics tasks. One popular multi-modal pair is cameras and laser scanners. To overlay and jointly use the data from both modalities, it is necessary to calibrate the sensors, i.e., to obtain the spatial relation between the sensors.Computing such a calibration is challenging as both sensors provide quite different data: cameras yield color or brightness information, laser scanners yield 3-D points. However, several laser scanners additionally provide reflectances, which turn out to make calibration to a camera well feasible. To this end, we first estimate a rough alignment of the coordinate systems of both modalities. Then, we use the laser scanner reflectances to compute a virtual image of the scene. Stereo calibration on the virtual image and the camera image are then used to compute a refined, high-accuracy calibration.It is encouraging that the accuracies in our experiments are comparable to camera-camera stereo setups and outperform another of other target-based calibration approach. This shows that the proposed algorithm reliably integrates the point cloud with the intensity image. As an example application, we use the calibration results to obtain ground-truth distance images for range cameras. Furthermore, we utilize this data to investigate the accuracy of the Microsoft Kinect V2 time-of-flight and the Intel RealSense R200 structured light camera.

Target Abundance-Based Fitness Screening (TAFiS) Facilitates Rapid Identification of Target-Specific and Physiologically Active Chemical Probes

Traditional approaches to drug discovery are frustratingly inefficient and have several key limitations that severely constrain our capacity to rapidly identify and develop novel experimental therapeutics. To address this, we have devised a second-generation target-based whole-cell screening assay based on the principles of competitive fitness, which can rapidly identify target-specific and physiologically active compounds. Briefly, strains expressing high, intermediate, and low levels of a preselected target protein are constructed, tagged with spectrally distinct fluorescent proteins (FPs), and pooled. The pooled strains are then grown in the presence of various small molecules, and the relative growth of each strain within the mixed culture is compared by measuring the intensity of the corresponding FP tags. Chemical-induced population shifts indicate that the bioactivity of a small molecule is dependent upon the target protein's abundance and thus establish a specific functional interaction. Here, we describe the molecular tools required to apply this technique in the prevalent human fungal pathogen Candida albicans and validate the approach using two well-characterized drug targets-lanosterol demethylase and dihydrofolate reductase. However, our approach, which we have termed target abundance-based fitness screening (TAFiS), should be applicable to a wide array of molecular targets and in essentially any genetically tractable microbe. IMPORTANCE Conventional drug screening typically employs either target-based or cell-based approaches. The first group relies on biochemical assays to detect modulators of a purified target. However, hits frequently lack drug-like characteristics such as membrane permeability and target specificity. Cell-based screens identify compounds that induce a desired phenotype, but the target is unknown, which severely restricts further development and optimization. To address these issues, we have developed a second-generation target-based whole-cell screening approach that incorporates the principles of both chemical genetics and competitive fitness, which enables the identification of target-specific and physiologically active compounds from a single screen. We have chosen to validate this approach using the important human fungal pathogen Candida albicans with the intention of pursuing novel antifungal targets. However, this approach is broadly applicable and is expected to dramatically reduce the time and resources required to progress from screening hit to lead compound.

A systematic analysis of FDA-approved anticancer drugs

BackgroundThe discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment. Repurposing existing drugs that may have unanticipated effects as potential candidates is one way to meet this important goal. Systematic investigation of efficient anticancer drugs could provide valuable insights into trends in the discovery of anticancer drugs, which may contribute to the systematic discovery of new anticancer drugs.ResultsIn this study, we collected and analyzed 150 anticancer drugs approved by the US Food and Drug Administration (FDA). Based on drug mechanism of action, these agents are divided into two groups: 61 cytotoxic-based drugs and 89 target-based drugs. We found that in the recent years, the proportion of targeted agents tended to be increasing, and the targeted drugs tended to be delivered as signal drugs. For 89 target-based drugs, we collected 102 effect-mediating drug targets in the human genome and found that most targets located on the plasma membrane and most of them belonged to the enzyme, especially tyrosine kinase. From above 150 drugs, we built a drug-cancer network, which contained 183 nodes (150 drugs and 33 cancer types) and 248 drug-cancer associations. The network indicated that the cytotoxic drugs tended to be used to treat more cancer types than targeted drugs. From 89 targeted drugs, we built a cancer-drug-target network, which contained 214 nodes (23 cancer types, 89 drugs, and 102 targets) and 313 edges (118 drug-cancer associations and 195 drug-target associations). Starting from the network, we discovered 133 novel drug-cancer associations among 52 drugs and 16 cancer types by applying the common target-based approach. Most novel drug-cancer associations (116, 87%) are supported by at least one clinical trial study.ConclusionsIn this study, we provided a comprehensive data source, including anticancer drugs and their targets and performed a detailed analysis in term of historical tendency and networks. Its application to identify novel drug-cancer associations demonstrated that the data collected in this study is promising to serve as a fundamental for anticancer drug repurposing and development.

The NAMPT/E2F2/SIRT1 axis promotes proliferation and inhibits p53-dependent apoptosis in human melanoma cells

Melanoma is the most common primary malignant neoplasm in adults, causing more deaths than any other skin cancer, necessitating the development of new target-based approaches. Current evidence suggests SIRT1, the mammalian nicotinamide adenine dinucleotide (NAD+)-dependent protein deacetylase, and nicotinamide phosphoribosyltransferase (NAMPT), the rate-limiting NAD+ biosynthetic enzyme, together comprise a novel systemic regulatory network to play a pivotal role in cell proliferation and apoptosis. Nevertheless, how the regulation of this cofactor interfaces with signal transduction network remains poorly understood in melanoma. Here, we report NAMPT is highly expressed in melanomaassociated with poor overall survival in patients. Pharmacological and genetic inhibition of NAMPT decreased NAD+ levels and melanoma cell proliferation capacity, and NAMPT knockdown induced apoptosis through the activity of the tumor suppressor p53. Next, we demonstrate NAMPT regulates the transcription factor E2F family member 2 (E2F2) in the apoptosis process. Downstream, E2F2 control the mRNA and protein levels of SIRT1. Finally, we find NAMPT mediates the apoptosis resistance of melanoma cells through NAMPT-E2F2-SIRT1 axis, more than NAD+-driven transcriptional program. Accordingly, our results demonstrated that NAMPT is a prognostic marker in melanoma, and the identificationofNAMPT-E2F2-SIRT1 pathway establishes another link between NAMPT and apoptosis events in melanoma, with therapeutic implications for this deadly cancer.

Nanoparticle-based strategies for cancer immunotherapy and immunodiagnostics.

Although recent successes in clinical trials are strengthening research focused on cancer immunology, the poor immunogenicity and off-target side effects of immunotherapeutics remain major challenges in translating these promising approaches to clinically feasible therapies in the treatment of a large range of tumors. Nanotechnology offers target-based approaches, which have shown significant improvements in the rapidly advancing field of cancer immunotherapy. Here, we first discuss the chemical and physical features of nanoparticulate systems that can be tuned to address the anticancer immune response, and then review recent, key examples of the exploited strategies, ranging from nanovaccines to NPs revising the tumor immunosuppressive microenvironment, up to immunotherapeutic multimodal NPs. Finally, the paper concludes by identifying the promising and outstanding challenges the field of emerging nanotechnologies is facing for cancer immunotherapy.

Linking High-Throughput Screens to Identify MoAs and Novel Inhibitors of Mycobacterium tuberculosis Dihydrofolate Reductase.

Though phenotypic and target-based high-throughput screening approaches have been employed to discover new antibiotics, the identification of promising therapeutic candidates remains challenging. Each approach provides different information, and understanding their results can provide hypotheses for a mechanism of action (MoA) and reveal actionable chemical matter. Here, we describe a framework for identifying efficacy targets of bioactive compounds. High throughput biophysical profiling against a broad range of targets coupled with machine learning was employed to identify chemical features with predicted efficacy targets for a given phenotypic screen. We validate the approach on data from a set of 55 000 compounds in 24 historical internal antibacterial phenotypic screens and 636 bacterial targets screened in high-throughput biophysical binding assays. Models were built to reveal the relationships between phenotype, target, and chemotype, which recapitulated mechanisms for known antibacterials. We also prospectively identified novel inhibitors of dihydrofolate reductase with nanomolar antibacterial efficacy against Mycobacterium tuberculosis. Molecular modeling provided structural insight into target-ligand interactions underlying selective killing activity toward mycobacteria over human cells.

How Phenotypic Screening Influenced Drug Discovery: Lessons from Five Years of Practice.

Since 2011, phenotypic screening has been a trend in the pharmaceutical industry as well as in academia. This renaissance was triggered by analyses that suggested that phenotypic screening is a superior strategy to discover first-in-class drugs. Despite these promises and considerable investments, pharmaceutical research organizations have encountered considerable challenges with the approach. Few success stories have emerged in the past 5 years and companies are questioning their investment in this area. In this contribution, we outline what we have learned about success factors and challenges of phenotypic screening. We then describe how our efforts in phenotypic screening have influenced our approach to drug discovery in general. We predict that concepts from phenotypic screening will be incorporated into target-based approaches and will thus remain influential beyond the current trend.

Reversal of cancer gene expression correlates with drug efficacy and reveals therapeutic targets

The decreasing cost of genomic technologies has enabled the molecular characterization of large-scale clinical disease samples and of molecular changes upon drug treatment in various disease models. Exploring methods to relate diseases to potentially efficacious drugs through various molecular features is critically important in the discovery of new therapeutics. Here we show that the potency of a drug to reverse cancer-associated gene expression changes positively correlates with that drug’s efficacy in preclinical models of breast, liver and colon cancers. Using a systems-based approach, we predict four compounds showing high potency to reverse gene expression in liver cancer and validate that all four compounds are effective in five liver cancer cell lines. The in vivo efficacy of pyrvinium pamoate is further confirmed in a subcutaneous xenograft model. In conclusion, this systems-based approach may be complementary to the traditional target-based approach in connecting diseases to potentially efficacious drugs.

Antimalarial Inhibitors Targeting Serine Hydroxymethyltransferase (SHMT) with in Vivo Efficacy and Analysis of their Binding Mode Based on X-ray Cocrystal Structures.

Target-based approaches toward new antimalarial treatments are highly valuable to prevent resistance development. We report several series of pyrazolopyran-based inhibitors targeting the enzyme serine hydroxymethyltransferase (SHMT), designed to improve microsomal metabolic stability and to identify suitable candidates for in vivo efficacy evaluation. The best ligands inhibited Plasmodium falciparum (Pf) and Arabidopsis thaliana (At) SHMT in target assays and PfNF54 strains in cell-based assays with values in the low nanomolar range (3.2-55 nM). A set of carboxylate derivatives demonstrated markedly improved in vitro metabolic stability (t1/2 > 2 h). A selected ligand showed significant in vivo efficacy with 73% of parasitemia reduction in a mouse model. Five new cocrystal structures with PvSHMT were solved at 2.3-2.6 Å resolution, revealing a unique water-mediated interaction with Tyr63 at the end of the para-aminobenzoate channel. They also displayed the high degree of conformational flexibility of the Cys364-loop lining this channel.

Neuroregeneration versus neurodegeneration: toward a paradigm shift in Alzheimer's disease drug discovery.

Alzheimer's disease represents an enormous global burden in terms of human suffering and economic cost. To tackle the current lack of effective drugs and the continuous clinical trial failures might require a shift from the prevailing paradigm targeting pathogenesis to the one targeting neural stem cells (NSCs) regeneration. In this context, small molecules have come to the forefront for their potential to manipulate NSCs, provide therapeutic tools and unveil NSCs biology. Classically, these molecules have been generated either by target-based or phenotypic approaches. To circumvent specific liabilities, nanomedicines emerge as a feasible alternative. However, this review is not intended to be comprehensive. Its purpose is to focus on recent examples that could accelerate development of neuroregenerative drugs against Alzheimer's disease.

Towards System Calibration of Panoramic Laser Scanners from a Single Station.

Terrestrial laser scanner measurements suffer from systematic errors due to internal misalignments. The magnitude of the resulting errors in the point cloud in many cases exceeds the magnitude of random errors. Hence, the task of calibrating a laser scanner is important for applications with high accuracy demands. This paper primarily addresses the case of panoramic terrestrial laser scanners. Herein, it is proven that most of the calibration parameters can be estimated from a single scanner station without a need for any reference information. This hypothesis is confirmed through an empirical experiment, which was conducted in a large machine hall using a Leica Scan Station P20 panoramic laser scanner. The calibration approach is based on the widely used target-based self-calibration approach, with small modifications. A new angular parameterization is used in order to implicitly introduce measurements in two faces of the instrument and for the implementation of calibration parameters describing genuine mechanical misalignments. Additionally, a computationally preferable calibration algorithm based on the two-face measurements is introduced. In the end, the calibration results are discussed, highlighting all necessary prerequisites for the scanner calibration from a single scanner station.

A Phenotypic Based Target Screening Approach Delivers New Antitubercular CTP Synthetase Inhibitors.

Despite its great potential, the target-based approach has been mostly unsuccessful in tuberculosis drug discovery, while whole cell phenotypic screening has delivered several active compounds. However, for many of these hits, the cellular target has not yet been identified, thus preventing further target-based optimization of the compounds. In this context, the newly validated drug target CTP synthetase PyrG was exploited to assess a target-based approach of already known, but untargeted, antimycobacterial compounds. To this purpose the publically available GlaxoSmithKline antimycobacterial compound set was assayed, uncovering a series of 4-(pyridin-2-yl)thiazole derivatives which efficiently inhibit the Mycobacterium tuberculosis PyrG enzyme activity, one of them showing low activity against the human CTP synthetase. The three best compounds were ATP binding site competitive inhibitors, with Ki values ranging from 3 to 20 μM, but did not show any activity against a small panel of different prokaryotic and eukaryotic kinases, thus demonstrating specificity for the CTP synthetases. Metabolic labeling experiments demonstrated that the compounds directly interfere not only with CTP biosynthesis, but also with other CTP dependent biochemical pathways, such as lipid biosynthesis. Moreover, using a M. tuberculosis pyrG conditional knock-down strain, it was shown that the activity of two compounds is dependent on the intracellular concentration of the CTP synthetase. All these results strongly suggest a role of PyrG as a target of these compounds, thus strengthening the value of this kind of approach for the identification of new scaffolds for drug development.

In silico polypharmacology of natural products.

Natural products with polypharmacological profiles have demonstrated promise as novel therapeutics for various complex diseases, including cancer. Currently, many gaps exist in our knowledge of which compounds interact with which targets, and experimentally testing all possible interactions is infeasible. Recent advances and developments of systems pharmacology and computational (in silico) approaches provide powerful tools for exploring the polypharmacological profiles of natural products. In this review, we introduce recent progresses and advances of computational tools and systems pharmacology approaches for identifying drug targets of natural products by focusing on the development of targeted cancer therapy. We survey the polypharmacological and systems immunology profiles of five representative natural products that are being considered as cancer therapies. We summarize various chemoinformatics, bioinformatics and systems biology resources for reconstructing drug-target networks of natural products. We then review currently available computational approaches and tools for prediction of drug-target interactions by focusing on five domains: target-based, ligand-based, chemogenomics-based, network-based and omics-based systems biology approaches. In addition, we describe a practical example of the application of systems pharmacology approaches by integrating the polypharmacology of natural products and large-scale cancer genomics data for the development of precision oncology under the systems biology framework. Finally, we highlight the promise of cancer immunotherapies and combination therapies that target tumor ecosystems (e.g. clones or 'selfish' sub-clones) via exploiting the immunological and inflammatory 'side' effects of natural products in the cancer post-genomics era.

Glycation potentiates α-synuclein-associated neurodegeneration in synucleinopathies.

α-Synuclein misfolding and aggregation is a hallmark in Parkinson's disease and in several other neurodegenerative diseases known as synucleinopathies. The toxic properties of α-synuclein are conserved from yeast to man, but the precise underpinnings of the cellular pathologies associated are still elusive, complicating the development of effective therapeutic strategies. Combining molecular genetics with target-based approaches, we established that glycation, an unavoidable age-associated post-translational modification, enhanced α-synuclein toxicity in vitro and in vivo, in Drosophila and in mice. Glycation affected primarily the N-terminal region of α-synuclein, reducing membrane binding, impaired the clearance of α-synuclein, and promoted the accumulation of toxic oligomers that impaired neuronal synaptic transmission. Strikingly, using glycation inhibitors, we demonstrated that normal clearance of α-synuclein was re-established, aggregation was reduced, and motor phenotypes in Drosophila were alleviated. Altogether, our study demonstrates glycation constitutes a novel drug target that can be explored in synucleinopathies as well as in other neurodegenerative conditions.

Plant Chemical Genetics: From Phenotype-Based Screens to Synthetic Biology.

The treatment of a biological system with small molecules to specifically perturb cellular functions is commonly referred to as chemical biology. Small molecules are used commercially as drugs, herbicides, and fungicides in different systems, but in recent years they are increasingly exploited as tools for basic research. For instance, chemical genetics involves the discovery of small-molecule effectors of various cellular functions through screens of compound libraries. Whereas the drug discovery field has largely been driven by target-based screening approaches followed by drug optimization, chemical genetics in plant systems tends to be fueled by more general phenotype-based screens, opening the possibility to identify a wide range of small molecules that are not necessarily directly linked to the process of interest. Here, we provide an overview of the current progress in chemical genetics in plants, with a focus on the discoveries regarding small molecules identified in screens designed with a basic biology perspective. We reflect on the possibilities that lie ahead and discuss some of the potential pitfalls that might be encountered upon adopting a given chemical genetics approach.

Biofocussed chemoprospecting: An efficient approach for drug discovery.

Drug discovery strategies include from broad random screening to focussed target-based approaches. Structure and substrate information greatly enables target-based design, but this is limited to relatively few targets; cell-based screening can identify new targets but often suffers from low hit rates and difficult hit optimization. Thus, newer approaches are needed that can improve the efficiency of screening and hit optimization. Here, we describe an efficient approach for hit generation, which may be called "biofocussed chemoprospecting." With bio-likeness and ease of synthesis as priority criteria, libraries may be constructed with good optimization potential, physicochemical diversity, drug likeness and low cost. Following this approach, two libraries based on linear and cyclic dipeptide scaffolds were designed, first as virtual libraries comprising of more than 30000 compounds, and after subsequent filtering, as a small library of a total of 51 compounds. These provided good diversity at low cost, and were tested for bioactivities. The discovery of six active compounds demonstrates a hit rate greater than 10%. This is comparable to target-based approaches, but the "chemoprospecting" method described here has the additional potential to identify new targets and mechanisms.

Applications of chemogenomic library screening in drug discovery.

The allure of phenotypic screening, combined with the industry preference for target-based approaches, has prompted the development of innovative chemical biology technologies that facilitate the identification of new therapeutic targets for accelerated drug discovery. A chemogenomic library is a collection of selective small-molecule pharmacological agents, and a hit from such a set in a phenotypic screen suggests that the annotated target or targets of that pharmacological agent may be involved in perturbing the observable phenotype. In this Review, we describe opportunities for chemogenomic screening to considerably expedite the conversion of phenotypic screening projects into target-based drug discovery approaches. Other applications are explored, including drug repositioning, predictive toxicology and the discovery of novel pharmacological modalities.

Multiview registration-based handheld 3D profiling system using visual navigation and structured light

ABSTRACTThis article describes the 3D handheld profiling system composed of a stereo camera and an illumination projector to collect high-resolution data for close range of applications. Visual navigation approach is either based on feature matching or on accurate target, and the target-based approach was found to be more accurate if the 3D object has less texture on its surface. Block matching algorithm was used to render the single-view 3D reconstruction. For multiview 3D modeling, coarse registration and final refinement of the point clouds using iterative closest point algorithm were utilized. The proposed approach yields good accuracy for multiview registration as demonstrated in the results of this research.

Animalistic dehumanization of older people by younger ones: Variations of humanness perceptions as a function of a target's age.

The present work investigated associations of older people with humanness. Focusing on complementary approaches (attribute-based, metaphor-based, and target-based), 4 studies tested the hypothesis that older people are the targets of animalistic dehumanization. Using an emotional attribution task, Study 1 (N = 112) explored infrahumanization and shows that young participants attributed more uniquely human emotions to young people than to older ones. No such effect occurred with regards to nonuniquely human emotions. Results of Study 2 (N = 62) replicated this result using a lexical-decision task. Using the metaphor-based approach, Study 3 (N = 99) confirmed that older people's dehumanization is restricted to its animalistic form and does not extend to the mechanistic one. Finally, in Study 4 (N = 167), we used a target-based approach and showed that characteristics initially attributed to older people are perceived as denoting lesser humanness than when these same characteristics are associated with younger people. Results of the 4 studies provide evidence for an animalistic form of dehumanization of older people by younger ones. Limits, implications, and future research are discussed. (PsycINFO Database Record

Apoptosis-independent organoruthenium anticancer complexes that overcome multidrug resistance: self-assembly and phenotypic screening strategies.

Multidrug resistance is a major impediment to chemotherapy and limits the efficacies of conventional anticancer drugs. A strategy to bypass multidrug resistance is to develop new drug candidates capable of inducing apoptosis-independent programmed cell death. However, cellular pathways implicated in alternative programmed cell death are not well-elucidated and multifactorial, making a target-based discovery approach a challenge. Here, we show that a coordination-directed three-component assembly and phenotypic screening strategy could be employed as a viable alternative for the identification of apoptosis-independent organoruthenium anticancer agents. Through an on-plate synthesis and screening of 195 organoruthenium complexes against apoptosis-sensitive and -resistant cancers, we identified two apoptosis-independent hits. Subsequent validation of the two hits showed a lack of induction of apoptotic biomarkers, a caspase-independent activity and an equal efficacy in both apoptosis-sensitive and -resistant colorectal cancers. This validated their apoptosis-independent modes-of-action, paving the way as potential candidates for the treatment of highly-refractory cancer phenotypes.