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

Open drug discovery in Alzheimer's disease

Alzheimer's disease (AD) drug discovery has focused on a set of highly studied therapeutic hypotheses, with limited success. The heterogeneous nature of AD processes suggests that a more diverse, systems-integrated strategy may identify new therapeutic hypotheses. Although many target hypotheses have arisen from systems-level modeling of human disease, in practice and for many reasons, it has proven challenging to translate them into drug discovery pipelines. First, many hypotheses implicate protein targets and/or biological mechanisms that are under-studied, meaning there is a paucity of evidence to inform experimental strategies as well as high-quality reagents to perform them. Second, systems-level targets are predicted to act in concert, requiring adaptations in how we characterize new drug targets. Here we posit that the development and open distribution of high-quality experimental reagents and informatic outputs-termed target enabling packages (TEPs)-will catalyze rapid evaluation of emerging systems-integrated targets in AD by enabling parallel, independent, and unencumbered research.

Designing drugs when there is low data availability: one-shot learning and other approaches to face the issues of a long-term concern

INTRODUCTION

Modern drug discovery generally is accessed by useful information from previous large databases or uncovering novel data. The lack of biological and/or chemical data tends to slow the development of scientific research and innovation. Here, approaches that may help provide solutions to generate or obtain enough relevant data or improve/accelerate existing methods within the last five years were reviewed.

AREAS COVERED

One-shot learning (OSL) approaches, structural modeling, molecular docking, scoring function space (SFS), molecular dynamics (MD), and quantum mechanics (QM) may be used to amplify the amount of available data to drug design and discovery campaigns, presenting methods, their perspectives, and discussions to be employed in the near future.

EXPERT OPINION

Recent works have successfully used these techniques to solve a range of issues in the face of data scarcity, including complex problems such as the challenging scenario of drug design aimed at intrinsically disordered proteins and the evaluation of potential adverse effects in a clinical scenario. These examples show that it is possible to improve and kickstart research from scarce available data to design and discover new potential drugs.

Novel Starting Points for Human Glycolate Oxidase Inhibitors, Revealed by Crystallography-Based Fragment Screening

Primary hyperoxaluria type I (PH1) is caused by AGXT gene mutations that decrease the functional activity of alanine:glyoxylate aminotransferase. A build-up of the enzyme’s substrate, glyoxylate, results in excessive deposition of calcium oxalate crystals in the renal tract, leading to debilitating renal failure. Oxidation of glycolate by glycolate oxidase (or hydroxy acid oxidase 1, HAO1) is a major cellular source of glyoxylate, and siRNA studies have shown phenotypic rescue of PH1 by the knockdown of HAO1, representing a promising inhibitor target. Here, we report the discovery and optimization of six low-molecular-weight fragments, identified by crystallography-based fragment screening, that bind to two different sites on the HAO1 structure: at the active site and an allosteric pocket above the active site. The active site fragments expand known scaffolds for substrate-mimetic inhibitors to include more chemically attractive molecules. The allosteric fragments represent the first report of non-orthosteric inhibition of any hydroxy acid oxidase and hold significant promise for improving inhibitor selectivity. The fragment hits were verified to bind and inhibit HAO1 in solution by fluorescence-based activity assay and surface plasmon resonance. Further optimization cycle by crystallography and biophysical assays have generated two hit compounds of micromolar (44 and 158 µM) potency that do not compete with the substrate and provide attractive starting points for the development of potent and selective HAO1 inhibitors.

Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins

Selectivity is a crucial property in small molecule development. Binding site comparisons within a protein family are a key piece of information when aiming to modulate the selectivity profile of a compound. Binding site differences can be exploited to confer selectivity for a specific target, while shared areas can provide insights into polypharmacology. As the quantity of structural data grows, automated methods are needed to process, summarize, and present these data to users. We present a computational method that provides quantitative and data-driven summaries of the available binding site information from an ensemble of structures of the same protein. The resulting ensemble maps identify the key interactions important for ligand binding in the ensemble. The comparison of ensemble maps of related proteins enables the identification of selectivity-determining regions within a protein family. We applied the method to three examples from the well-researched human bromodomain and kinase families, demonstrating that the method is able to identify selectivity-determining regions that have been used to introduce selectivity in past drug discovery campaigns. We then illustrate how the resulting maps can be used to automate comparisons across a target protein family.

Fragment Screening Reveals Starting Points for Rational Design of Galactokinase 1 Inhibitors to Treat Classic Galactosemia

Classic galactosemia is caused by loss-of-function mutations in galactose-1-phosphate uridylyltransferase (GALT) that lead to toxic accumulation of its substrate, galactose-1-phosphate. One proposed therapy is to inhibit the biosynthesis of galactose-1-phosphate, catalyzed by galactokinase 1 (GALK1). Existing inhibitors of human GALK1 (hGALK1) are primarily ATP-competitive with limited clinical utility to date. Here, we determined crystal structures of hGALK1 bound with reported ATP-competitive inhibitors of the spiro-benzoxazole series, to reveal their binding mode in the active site. Spurred by the need for additional chemotypes of hGALK1 inhibitors, desirably targeting a nonorthosteric site, we also performed crystallography-based screening by soaking hundreds of hGALK1 crystals, already containing active site ligands, with fragments from a custom library. Two fragments were found to bind close to the ATP binding site, and a further eight were found in a hotspot distal from the active site, highlighting the strength of this method in identifying previously uncharacterized allosteric sites. To generate inhibitors of improved potency and selectivity targeting the newly identified binding hotspot, new compounds were designed by merging overlapping fragments. This yielded two micromolar inhibitors of hGALK1 that were not competitive with respect to either substrate (ATP or galactose) and demonstrated good selectivity over hGALK1 homologues, galactokinase 2 and mevalonate kinase. Our findings are therefore the first to demonstrate inhibition of hGALK1 from an allosteric site, with potential for further development of potent and selective inhibitors to provide novel therapeutics for classic galactosemia.

Structure driven compound optimization in targeted protein degradation

Small molecule induced protein degradation has created tremendous excitement in drug discovery within recent years. Not being confined to target inhibition and being able to remove disease-causing protein targets via engagement and subsequent ubiquitination has provided scientists with a powerful tool to expand the druggable space. At the center of this approach sits the ternary complex formed between an E3 ubiquitin ligase, the small molecule degrader, and the target protein. A productive ternary complex is pivotal for a ubiquitin to be transferred to a surface lysine of the target protein resulting in poly-ubiquitination which enables recognition and finally degradation by the proteasome. As understanding the ternary complex means understanding the degradation process, many efforts are put into obtaining structural information of the ternary complex and getting a snapshot of the underlying conformations and molecular contacts. Locking this transient trimeric intermediate in a crystalline state has proven to be very demanding but the obtained results have tremendously improved our understanding of small molecule degraders. This review discusses target protein degradation from a structural perspective and highlights the evolution of certain degraders based on the obtained structural insights.

Open Targets Platform: new developments and updates two years on

The Open Targets Platform integrates evidence from genetics, genomics, transcriptomics, drugs, animal models and scientific literature to score and rank target-disease associations for drug target identification. The associations are displayed in an intuitive user interface (https://www.targetvalidation.org), and are available through a REST-API (https://api.opentargets.io/v3/platform/docs/swagger-ui) and a bulk download (https://www.targetvalidation.org/downloads/data). In addition to target-disease associations, we also aggregate and display data at the target and disease levels to aid target prioritisation. Since our first publication two years ago, we have made eight releases, added new data sources for target-disease associations, started including causal genetic variants from non genome-wide targeted arrays, added new target and disease annotations, launched new visualisations and improved existing ones and released a new web tool for batch search of up to 200 targets. We have a new URL for the Open Targets Platform REST-API, new REST endpoints and also removed the need for authorisation for API fair use. Here, we present the latest developments of the Open Targets Platform, expanding the evidence and target-disease associations with new and improved data sources, refining data quality, enhancing website usability, and increasing our user base with our training workshops, user support, social media and bioinformatics forum engagement.

Substrate reduction therapy for inborn errors of metabolism

Inborn errors of metabolism (IEM) represent a growing group of monogenic disorders each associated with inherited defects in a metabolic enzyme or regulatory protein, leading to biochemical abnormalities arising from a metabolic block. Despite the well-established genetic linkage, pathophysiology and clinical manifestations for many IEMs, there remains a lack of transformative therapy. The available treatment and management options for a few IEMs are often ineffective or expensive, incurring a significant burden to individual, family, and society. The lack of IEM therapies, in large part, relates to the conceptual challenge that IEMs are loss-of-function defects arising from the defective enzyme, rendering pharmacologic rescue difficult. An emerging approach that holds promise and is the subject of a flurry of pre-/clinical applications, is substrate reduction therapy (SRT). SRT addresses a common IEM phenotype associated with toxic accumulation of substrate from the defective enzyme, by inhibiting the formation of the substrate instead of directly repairing the defective enzyme. This minireview will summarize recent highlights towards the development of emerging SRT, with focussed attention towards repurposing of currently approved drugs, approaches to validate novel targets and screen for hit molecules, as well as emerging advances in gene silencing as a therapeutic modality.

Signaling through non-membrane nuclear phosphoinositide binding proteins in human health and disease

Phosphoinositide membrane signaling is critical for normal physiology, playing well-known roles in diverse human pathologies. The basic mechanisms governing phosphoinositide signaling within the nucleus, however, have remained deeply enigmatic owing to their presence outside the nuclear membranes. Over 40% of nuclear phosphoinositides can exist in this non-membrane state, held soluble in the nucleoplasm by nuclear proteins that remain largely unidentified. Recently, two nuclear proteins responsible for solubilizing phosphoinositides were identified, steroidogenic factor-1 (SF-1; NR5A1) and liver receptor homolog-1 (LRH-1; NR5A2), along with two enzymes that directly remodel these phosphoinositide/protein complexes, phosphatase and tensin homolog (PTEN; MMAC) and inositol polyphosphate multikinase (IPMK; ipk2). These new footholds now permit the assignment of physiological functions for nuclear phosphoinositides in human diseases, such as endometriosis, nonalcoholic fatty liver disease/steatohepatitis, glioblastoma, and hepatocellular carcinoma. The unique nature of nuclear phosphoinositide signaling affords extraordinary clinical opportunities for new biomarkers, diagnostics, and therapeutics. Thus, phosphoinositide biology within the nucleus may represent the next generation of low-hanging fruit for new drugs, not unlike what has occurred for membrane phosphatidylinositol 3-kinase drug development. This review connects recent basic science discoveries in nuclear phosphoinositide signaling to clinical pathologies, with the hope of inspiring development of new therapies.

Structure-based drug design: aiming for a perfect fit

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.