Worming our way to novel drug discovery with the Caenorhabditis elegans proteostasis network,stress response and insulin-signaling pathways

Introduction: Many human diseases result from a failure of a single protein to achieve the correct folding and tertiary conformation. These so-called ‘conformational diseases’ involve diverse proteins and distinctive cellular pathologies. They all engage the proteostasis network (PN), to varying degrees in an attempt to mange cellular stress and restore protein homeostasis. The insulin/insulin-like growth factor signaling (IIS) pathway is a master regulator of cellular stress response, which is implicated in regulating components of the PN.

Areas covered: This review focuses on novel approaches to target conformational diseases. The authors discuss the evidence supporting the involvement of the IIS pathway in modulating the PN and regulating proteostasis in Caenorhabditis elegans. Furthermore, they review previous PN and IIS drug screens and explore the possibility of using C. elegans for whole organism-based drug discovery for modulators of IIS-proteostasis pathways.

Expert opinion: An alternative approach to develop individualized therapy for each conformational disease is to modulate the global PN. The involvement of the IIS pathway in regulating longevity and response to a variety of stresses is well documented. Increasing data now provide evidence for the close association between the IIS and the PN pathways. The authors believe that high-throughput screening campaigns, which target the C. elegans IIS pathway, may identify drugs that are efficacious in treating numerous conformational diseases.     

Automated docking for novel drug discovery

Introduction: The volume of three-dimensional structural information of macromolecules and the number of computational tools to predict binding modes and affinities of molecular complexes are increasing daily. Molecular docking is a rational structural approach employed to predict thermodynamic parameters based on molecular recognition between two or more molecules. In addition, docking studies have become very important for therapeutic applications in modern structure-based drug design because this computational tool uses few economic resources. However, they omit many biological conditions that critically influence small and macromolecular structural motions. To mimic physiological conditions, it is necessary to consider other environmental factors, such as the presence of water molecules and the flexibility of ligands and side chain residues of proteins. Furthermore, molecular dynamics simulations have been coupled with docking procedures to expand the boundaries and obtain more reliable information.

Areas covered: In this article, we review current advances in protein-small molecule docking and possible future directions.

Expert opinion: Docking studies include many conformations to predict binding free energies (scoring functions) and to search (scoring sampling) for the most representative binding conformations. Therefore, several biological properties, from side chain residues to complete protein motions, have been included in docking studies to improve theoretical predictions.     

Strategies for drug discovery by targeting sulfation pathways

Posttranslational modifications of proteins such as phosphorylation have been recognized as pivotal modulators of biological activity in healthy and diseased tissues. Sulfation is a key posttranslational modification the role of which in physiology and pathology is only now becoming appreciated. Whereas phosphorylation is central to intracellular signal transduction, sulfation modulates cell-cell and cell-matrix communication. Sulfation involves a class of enzymes known as sulfotransferases, which transfer sulfate from the ATP-like sulfate donor 3'phosphoadenosine-5'phosphosulate to glycoproteins, glycolipids or metabolites. This review focuses on Golgi-localized sulfotransferases, their molecular biology and biochemistry, and strategies towards discovery of sulfotransferase inhibitors that could have potential as therapeutics in inflammation, cancer and infectious diseases.     

Development of novel benzotriazines for drug discovery

Background: The synthesis of novel benzotriazine heterocycles was developed independently around the same time by Bischler, Bamberger and Arndt. Over the years, different groups have reported the synthesis of benzotriazine based compounds. Objective: This literature review gives an update on recent benzotriazine compounds and their applications. Conclusion: The benzotriazine core has been used in various drug discovery projects including anticancer, anti-inflammatory and antimalarial programs. Recently, the benzotriazine core was used to develop selective kinase inhibitors targeting SRC, VEGFr2, BCR-ABL and BCR-ABL-T315I. Two benzotriazine based compounds, tirapazamine for the treatment of cancer and TG100801 for the treatment of age-related macular degeneration, have entered clinical trials.     

Colorectal cancer models for novel drug discovery

Introduction: Despite increased screening rates and advances in targeted therapy, colorectal cancer (CRC) remains the third leading cause of cancer-related mortality. CRC models that recapitulate key features of human disease are essential to the development of novel and effective therapeutics. Classic methods of modeling CRC such as human cell lines and xenograft mice, while useful for many applications, carry significant limitations. Recently developed in vitro and in vivo models overcome some of these deficiencies and thus can be utilized to better model CRC for mechanistic and translational research.

Areas covered: The authors review established models of in vitro cell culture and describe advances in organoid culture for studying normal and malignant intestine. They also discuss key features of classic xenograft models and describe other approaches for in vivo CRC research, including patient-derived xenograft, carcinogen-induced, orthotopic transplantation and transgenic mouse models. We also describe mouse models of metastatic CRC.

Expert opinion: No single model is optimal for drug discovery in CRC. Genetically engineered models overcome many limitations of xenograft models. Three-dimensional organoids can be efficiently derived from both normal and malignant tissue for large-scale in vitro and in vivo (transplantation) studies and are thus a significant advance in CRC drug discovery.     

Identification of disease-relevant genes for molecularly-targeted drug discovery

The current paradigm for cancer therapy is undergoing a change from non-specific cytotoxic agents to more specific approaches based on unique molecular features of cancer cells. The identification and validation of disease relevant targets are crucial for the development of molecularly targeted anticancer therapies. Advances in our understanding of the molecular basis of cancer together with novel approaches to interfere with signal transduction pathways have opened new horizons for anticancer target discovery. In particular, the image-based large scale analysis of cellular phenotypes that arise from genetic or chemical perturbations paved the way for the identification and validation of disease relevant molecular targets independent of preconceived notions of mechanistic relationships. In addition, novel and sophisticated techniques of genome manipulation allow for the use of mouse models that faithfully recapitulate critical elements of human cancer for target validation in vivo. We believe that these advances will translate into more and better validated drug targets.     

Clinical metabolomics paves the way towards future healthcare strategies

Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation.     

Computational modeling in melanoma for novel drug discovery

ABSTRACT

Introduction: There is a growing body of evidence highlighting the applications of computational modeling in the field of biomedicine. It has recently been applied to the in silico analysis of cancer dynamics. In the era of precision medicine, this analysis may allow the discovery of new molecular targets useful for the design of novel therapies and for overcoming resistance to anticancer drugs. According to its molecular behavior, melanoma represents an interesting tumor model in which computational modeling can be applied. Melanoma is an aggressive tumor of the skin with a poor prognosis for patients with advanced disease as it is resistant to current therapeutic approaches.

Areas covered: This review discusses the basics of computational modeling in melanoma drug discovery and development. Discussion includes the in silico discovery of novel molecular drug targets, the optimization of immunotherapies and personalized medicine trials.

Expert opinion: Mathematical and computational models are gradually being used to help understand biomedical data produced by high-throughput analysis. The use of advanced computer models allowing the simulation of complex biological processes provides hypotheses and supports experimental design. The research in fighting aggressive cancers, such as melanoma, is making great strides. Computational models represent the key component to complement these efforts. Due to the combinatorial complexity of new drug discovery, a systematic approach based only on experimentation is not possible. Computational and mathematical models are necessary for bringing cancer drug discovery into the era of omics, big data and personalized medicine.     

Using quantitative systems pharmacology for novel drug discovery

Introduction: Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology.

Areas covered: This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider ‘systems-level’ context in order to design new drugs with improved efficacy and fewer unwanted off-target effects.

Expert opinion: The use of network biology produces valuable information such as new indications for approved drugs, drug–drug interactions, proteins–drug side effects and pathways–gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from ‘one molecule for one target to give one therapeutic effect’ to the ‘big systems-based picture’ seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.     

Developments with bead-based screening for novel drug discovery

ABSTRACT

Introduction: Combinatorial chemistry provides a cost-effective method for rapid discovery of drug hits/leads. The one-bead-one-compound (OBOC) library method is in principle ideally suited for this application, because it permits a large number of structurally diverse compounds to be rapidly synthesized and simultaneously screened for binding to a target of interest. However, application of OBOC libraries in drug discovery has encountered significant technical challenges.

Areas covered: This Special Report covers the challenges associated with first-generation OBOC libraries (difficulty in structural identification of non-peptidic hits, screening biases and high false positive rates, and poor scalability). It also covers the many strategies developed over the past two decades to overcome these challenges.

Expert opinion: With most of the technical challenges now overcome and the advent of powerful intracellular delivery technologies, OBOC libraries of metabolically stable and conformationally rigidified molecules (macrocyclic peptides and peptidomimetics, rigidified acyclic oligomers, and D-peptides) can be routinely synthesized and screened to discover initial hits against previously undruggable targets such as intracellular protein-protein interactions. On the other hand, further developments are still needed to expand the utility of the OBOC method to non-peptidic chemical scaffolds.     

Stem cell signaling as a target for novel drug discovery: recent progress in the WNT and Hedgehog pathways

One of the most exciting fields in biomedical research over the past few years is stem cell biology, and therapeutic application of stem cells to replace the diseased or damaged tissues is also an active area in development. Although stem cell therapy has a number of technical challenges and regulatory hurdles to overcome, the use of stem cells as tools in drug discovery supported by mature technologies and established regulatory paths is expected to generate more immediate returns. In particular, the targeting of stem cell signaling pathways is opening up a new avenue for drug discovery. Aberrations in these pathways result in various diseases, including cancer, fibrosis and degenerative diseases. A number of drug targets in stem cell signaling pathways have been identified. Among them, WNT and Hedgehog are two most important signaling pathways, which are the focus of this review. A hedgehog pathway inhibitor, vismodegib (Erivedge), has recently been approved by the US FDA for the treatment of skin cancer, while several drug candidates for the WNT pathway are entering clinical trials. We have discovered that the stem cell signaling pathways respond to traditional Chinese medicines. Substances isolated from herbal medicine may act specifically on components of stem cell signaling pathways with high affinities. As many of these events can be explained through molecular interactions, these phenomena suggest that discovery of stem cell-targeting drugs from natural products may prove to be highly successful.     

Molecular topology as a novel approach for drug discovery

Introduction: Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. One key part of MT is that, in the process of drug design/discovery, there is no need for an explicit knowledge of a drug's mechanism of action unlike other drug discovery methods.

Areas covered: In this review, the authors introduce the topic by explaining briefly the most common methodology used today in drug design/discovery and address the most important concepts of MT and the methodology followed (QSAR equations, LDA, etc.). Furthermore, the significant results achieved, from this approach, are outlined and discussed.

Expert opinion: The results outlined herein can be explained by considering that MT represents a new paradigm in the field of drug design. This means that it is not only an alternative method to the conventional methods, but it is also independent, that is, it represents a pathway to connect directly molecular structure with the experimental properties of the compounds (particularly drugs). Moreover, the process can be realized also in the reverse pathway, that is, designing new molecules from their topological pattern, what opens almost limitless expectations in new drugs development, given that the virtual universe of molecules is much greater than that of the existing ones.     

FtsZ: a novel target for tuberculosis drug discovery

The emergence of multi-drug resistant Mycobacterium tuberculosis (Mtb) strains has made many of the currently available anti-TB drugs ineffective. Accordingly there is a pressing need to identify new drug targets. FtsZ, a bacterial tubulin homologue, is an essential cell division protein that polymerizes in a GTP-dependent manner, forming a highly dynamic cytokinetic ring, designated as the Z ring, at the septum site. Following recruitment of other cell division proteins, the Z ring contracts, resulting in closure of the septum and then formation of two daughter cells. Since inactivation of FtsZ or alteration of FtsZ assembly results in the inhibition of Z ring and septum formation, FtsZ is a very promising target for new antimicrobial drug development. This review describes the function and dynamic behaviors of FtsZ, its homology to tubulin, and recent development of FtsZ inhibitors as potential anti-TB agents.     

Developments with 3D bioprinting for novel drug discovery

ABSTRACT

Introduction: Although there have been significant contributions from the pharmaceutical industry to clinical practice, several diseases remain unconquered, with the discovery of new drugs remaining a paramount objective. The actual process of drug discovery involves many steps including pre-clinical and clinical testing, which are highly time- and resource-consuming, driving researchers to improve the process efficiency. The shift of modelling technology from two-dimensions (2D) to three-dimensions (3D) is one of such advancements. 3D Models allow for close mimicry of cellular interactions and tissue microenvironments thereby improving the accuracy of results. The advent of bioprinting for fabrication of tissues has shown potential to improve 3D culture models.

Areas covered: The present review provides a comprehensive update on a wide range of bioprinted tissue models and appraise them for their potential use in drug discovery research.

Expert opinion: Efficiency, reproducibility, and standardization are some impediments of the bioprinted models. Vascularization of the constructs has to be addressed in the near future. While much progress has already been made with several seminal works, the next milestone will be the commercialization of these models after due regulatory approval.     

Intrinsically disordered proteins and novel strategies for drug discovery

Introduction: There is a natural abundance of intrinsically disordered proteins or intrinsically disordered protein regions (IDPs or IDPRs), that is, biologically active proteins/regions without stable structure. Their wide functional repertoire; the ability to participate in multiple interactions; the capability to fold at binding in a template-dependent manner and their common involvement in the pathogenesis of numerous human diseases suggest that these proteins should be seriously considered as novel drug targets.

Areas covered: This article describes the major classes of ordered proteins traditionally used as drug targets and introduces the molecular mechanisms of drugs targeting ordered proteins. Furthermore, it illustrates basic ways of rational drug design for these proteins, and shows why these approaches cannot be directly used for intrinsic disorder-based drug design. Some of the new approaches utilized for finding drugs targeting IDPs/IDPRs are introduced.

Expert opinion: There is a continuing progress in the design of small molecules for IDPs/IDPRs and several small molecules are found that specifically inhibit the disorder-based interaction of IDPs with their numerous partners. It is expected that the initial studies will be extended and novel intrinsic disorder-based drug design approaches will be developed. Furthermore, putative new targets will be identified, and a better understanding of the molecular mechanisms underlying modulation of promiscuous IDP binding will be achieved.