A practical Java tool for small-molecule compound appraisal

The increased use of small-molecule compound screening by new users from a variety of different academic backgrounds calls for adequate software to administer, appraise, analyse and exchange information obtained from screening experiments. While software and spreadsheet solutions exist, there is a need for software that can be easily deployed and is convenient to use.The Java application cApp addresses this need and aids in the handling and storage of information on small-molecule compounds. The software is intended for the appraisal of compounds with respect to their physico-chemical properties, analysis in relation to adherence to likeness rules as well as recognition of pan-assay interference components and cross-linking with identical entries in the PubChem Compound Database. Results are displayed in a tabular form in a graphical interface, but can also be written in an HTML or PDF format. The output of data in ASCII format allows for further processing of data using other suitable programs. Other features include similarity searches against user-provided compound libraries and the PubChem Compound Database, as well as compound clustering based on a MaxMin algorithm.cApp is a personal database solution for small-molecule compounds which can handle all major chemical formats. Being a standalone software, it has no other dependency than the Java virtual machine and is thus conveniently deployed. It streamlines the analysis of molecules with respect to physico-chemical properties and drug discovery criteria; cApp is distributed under the GNU Affero General Public License version 3 and available from http://www.structuralchemistry.org/pcsb/. To download cApp, users will be asked for their name, institution and email address. A detailed manual can also be downloaded from this site, and online tutorials are available at http://www.structuralchemistry.org/pcsb/capp.php

The Impact of Small Molecule Binding on the Energy Landscape of the Intrinsically Disordered Protein C-Myc

Intrinsically disordered proteins are attractive therapeutic targets owing to their prevalence in several diseases. Yet their lack of well-defined structure renders ligand discovery a challenging task. An intriguing example is provided by the oncoprotein c-Myc, a transcription factor that is over expressed in a broad range of cancers. Transcriptional activity of c-Myc is dependent on heterodimerization with partner protein Max. This protein-protein interaction is disrupted by the small molecule 10058-F4 (1), that binds to monomeric and disordered c-Myc. To rationalize the mechanism of inhibition, structural ensembles for the segment of the c-Myc domain that binds to 1 were computed in the absence and presence of the ligand using classical force fields and explicit solvent metadynamics molecular simulations. The accuracy of the computed structural ensembles was assessed by comparison of predicted and measured NMR chemical shifts. The small molecule 1 was found to perturb the composition of the apo equilibrium ensemble and to bind weakly to multiple distinct c-Myc conformations. Comparison of the apo and holo equilibrium ensembles reveals that the c-Myc conformations binding 1 are already partially formed in the apo ensemble, suggesting that 1 binds to c-Myc through an extended conformational selection mechanism. The present results have important implications for rational ligand design efforts targeting intrinsically disordered proteins

Small molecules, big targets: drug discovery faces the protein-protein interaction challenge.

Protein-protein interactions (PPIs) are of pivotal importance in the regulation of biological systems and are consequently implicated in the development of disease states. Recent work has begun to show that, with the right tools, certain classes of PPI can yield to the efforts of medicinal chemists to develop inhibitors, and the first PPI inhibitors have reached clinical development. In this Review, we describe the research leading to these breakthroughs and highlight the existence of groups of structurally related PPIs within the PPI target class. For each of these groups, we use examples of successful discovery efforts to illustrate the research strategies that have proved most useful.JS, DES and ARB thank the Wellcome Trust for funding.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nrd.2016.2

Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease

COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments were progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease

The distribution of standard deviations applied to high throughput screening

High throughput screening (HTS) assesses compound libraries for “activity” using target assays. A subset of HTS data contains a large number of sample measurements replicated a small number of times providing an opportunity to introduce the distribution of standard deviations (DSD). Applying the DSD to some HTS data sets revealed signs of bias in some of the data and discovered a sub-population of compounds exhibiting high variability which may be difficult to screen. In the data examined, 21% of 1189 such compounds were pan-assay interference compounds. This proportion reached 57% for the most closely related compounds within the sub-population. Using the DSD, large HTS data sets can be modelled in many cases as two distributions: a large group of nearly normally distributed “inactive” compounds and a residual distribution of “active” compounds. The latter were not normally distributed, overlapped inactive distributions – on both sides –, and were larger than typically assumed. As such, a large number of compounds are being misclassified as “inactive” or are invisible to current methods which could become the next generation of drugs. Although applied here to HTS, it is applicable to data sets with a large number of samples measured a small number of times

Oligosaccharyltransferase Inhibition Induces Senescence in RTK-Driven Tumor Cells

Asparagine (N)-linked glycosylation is a protein modification critical for glycoprotein folding, stability, and cellular localization. To identify small molecules that inhibit new targets in this biosynthetic pathway, we initiated a cell-based high throughput screen and lead compound optimization campaign that delivered a cell permeable inhibitor (NGI-1). NGI-1 targets the oligosaccharyltransferase (OST), a hetero-oligomeric enzyme that exists in multiple isoforms and transfers oligosaccharides to recipient proteins. In non-small cell lung cancer cells NGI-1 blocks cell surface localization and signaling of the EGFR glycoprotein, but selectively arrests proliferation in only those cell lines that are dependent on EGFR (or FGFR) for survival. In these cell lines OST inhibition causes cell cycle arrest accompanied by induction of p21, autofluorescence, and changes in cell morphology; all hallmarks of senescence. These results identify OST inhibition as a potential therapeutic approach for treating receptor tyrosine kinase-dependent tumors and provides a chemical probe for reversibly regulating N-linked glycosylation in mammalian cells

Natural products as starting points for future anti-malarial therapies: going back to our roots?

Abstract Background The discovery and development of new anti-malarials are at a crossroads. Fixed dose artemisinin combination therapy is now being used to treat a hundred million children each year, with a cost as low as 30 cents per child, with cure rates of over 95%. However, as with all anti-infective strategies, this triumph brings with it the seeds of its own downfall, the emergence of resistance. It takes ten years to develop a new medicine. New classes of medicines to combat malaria, as a result of infection by Plasmodium falciparum and Plasmodium vivax are urgently needed. Results Natural product scaffolds have been the basis of the majority of current anti-malarial medicines. Molecules such as quinine, lapachol and artemisinin were originally isolated from herbal medicinal products. After improvement with medicinal chemistry and formulation technologies, and combination with other active ingredients, they now make up the current armamentarium of medicines. In recent years advances in screening technologies have allowed testing of millions of compounds from pharmaceutical diversity for anti-malarial activity in cellular assays. These initiatives have resulted in thousands of new sub-micromolar active compounds – starting points for new drug discovery programmes. Against this backdrop, the paucity of potent natural products identified has been disappointing. Now is a good time to reflect on the current approach to screening herbal medicinal products and suggest revisions. Nearly sixty years ago, the Chinese doctor Chen Guofu, suggested natural products should be approached by dao-xing-ni-shi or ‘acting in the reversed order’, starting with observational clinical studies. Natural products based on herbal remedies are in use in the community, and have the potential unique advantage that clinical observational data exist, or can be generated. The first step should be the confirmation and definition of the clinical activity of herbal medicinal products already used by the community. This first step forms a solid basis of observations, before moving to in vivo pharmacological characterization and ultimately identifying the active ingredient. A large part of the population uses herbal medicinal products despite limited numbers of well-controlled clinical studies. Increased awareness by the regulators and public health bodies of the need for safety information on herbal medicinal products also lends support to obtaining more clinical data on such products. Conclusions The relative paucity of new herbal medicinal product scaffolds active against malaria results discovered in recent years suggest it is time to re-evaluate the ‘smash and grab’ approach of randomly testing purified natural products and replace it with a patient-data led approach. This will require a change of perspective form many in the field. It will require an investment in standardisation in several areas, including: the ethnopharmacology and design and reporting of clinical observation studies, systems for characterizing anti-malarial activity of patient plasma samples ex vivo followed by chemical and pharmacological characterisation of extracts from promising sources. Such work falls outside of the core mandate of the product development partnerships, such as MMV, and so will require additional support. This call is timely, given the strong interest from researchers in disease endemic countries to support the research arm of a malaria eradication agenda. Para-national institutions such as the African Network for Drugs and Diagnostics Innovation (ANDi) will play a major role in facilitating the development of their natural products patrimony and possibly clinical best practice to bring forward new therapeutics. As in the past, with quinine, lapinone and artemisinin, once the activity of herbal medicinal products in humans is characterised, it can be used to identify new molecular scaffolds which will form the basis of the next generation of anti-malarial therapies.</p

Target 2035-update on the quest for a probe for every protein

Twenty years after the publication of the first draft of the human genome, our knowledge of the human proteome is still fragmented. The challenge of translating the wealth of new knowledge from genomics into new medicines is that proteins, and not genes, are the primary executers of biological function. Therefore, much of how biology works in health and disease must be understood through the lens of protein function. Accordingly, a subset of human proteins has been at the heart of research interests of scientists over the centuries, and we have accumulated varying degrees of knowledge about approximately 65% of the human proteome. Nevertheless, a large proportion of proteins in the human proteome (∼35%) remains uncharacterized, and less than 5% of the human proteome has been successfully targeted for drug discovery. This highlights the profound disconnect between our abilities to obtain genetic information and subsequent development of effective medicines. Target 2035 is an international federation of biomedical scientists from the public and private sectors, which aims to address this gap by developing and applying new technologies to create by year 2035 chemogenomic libraries, chemical probes, and/or biological probes for the entire human proteome

An in vivo platform for identifying inhibitors of protein aggregation

Protein aggregation underlies an array of human diseases, yet only one small molecule therapeutic has been successfully developed to date. Here, we introduce an in vivo system, based on a β-lactamase tripartite fusion construct, capable of identifying aggregation-prone sequences in the periplasm of Escherichia coli and inhibitors that prevent their aberrant self-assembly. We demonstrate the power of the system using a range of proteins, from small unstructured peptides (islet amyloid polypeptide and amyloid β) to larger, folded immunoglobulin domains. Configured in a 48-well format, the split β-lactamase sensor readily differentiates between aggregation-prone and soluble sequences. Performing the assay in the presence of 109 compounds enabled a rank ordering of inhibition and revealed a new inhibitor of IAPP aggregation. This platform can be applied to both amyloidogenic and other aggregation-prone systems, independent of sequence or size, and can identify small molecules or other factors able to ameliorate or inhibit protein aggregation