CcpNmr AnalysisScreen, a new software programme with dedicated automated analysis tools for fragment-based drug discovery by NMR

Accelerating BRPF1b hit identification with BioPhysical and Active Learning Screening (BioPALS)

We report the development of BioPhysical and Active Learning Screening (BioPALS); a rapid and versatile hit identification protocol combining AI-powered virtual screening with a GCI-driven biophysical confirmation workflow. Its application to the BRPF1b bromodomain afforded a range of novel micromolar binders with favorable ADMET properties. In addition to the excellent in silico/in vitro confirmation rate demonstrated with BRPF1b, binding kinetics were determined, and binding topologies predicted for all hits. BioPALS is a lean, data-rich, and standardized approach to hit identification applicable to a wide range of biological targets.

Biophysical and Structural Characterization of the Interaction between Human Galectin-3 and the Lipopolysaccharide from Pseudomonas aeruginosa

Given the significant involvement of galectins in the development of numerous diseases, the aim of the following work is to further study the interaction between galectin-3 (Gal3) and the LPS from Pseudomonas aeruginosa. This manuscript focused on the study of the interaction of the carbohydrate recognition domain of Gal3 with the LPS from Pseudomonas aeruginosa by means of different complementary methodologies, such as circular dichroism; spectrofluorimetry; dynamic and static light scattering and evaluation of the impact of Gal3 on the redox potential membranes of Escherichia coli and P. aeruginosa cells, as well as ITC and NMR studies. This thorough investigation reinforces the hypothesis of an interaction between Gal3 and LPS, unraveling the structural details and providing valuable insights into the formation of these intricate molecular complexes. Taken together, these achievements could potentially prompt the design of therapeutic drugs useful for the development of agonists and/or antagonists for LPS receptors such as galectins as adjunctive therapy for P. aeruginosa.

Selective inhibition of cannabinoid CB1 receptor-evoked signalling by the interacting protein GAP43

Cannabinoids exert pleiotropic effects on the brain by engaging the cannabinoid CB1 receptor (CB1R), a presynaptic metabotropic receptor that regulates key neuronal functions in a highly context-dependent manner. We have previously shown that CB1R interacts with growth-associated protein of 43 kDa (GAP43) and that this interaction inhibits CB1R function on hippocampal excitatory synaptic transmission, thereby impairing the therapeutic effect of cannabinoids on epileptic seizures in vivo. However, the underlying molecular features of this interaction remain unexplored. Here, we conducted mechanistic experiments on HEK293T cells co-expressing CB1R and GAP43 and show that GAP43 modulates CB1R signalling in a strikingly selective manner. Specifically, GAP43 did not affect the archetypical agonist-evoked (i) CB1R/Gi/o protein-coupled signalling pathways, such as cAMP/PKA and ERK, or (ii) CB1R internalization and intracellular trafficking. In contrast, GAP43 blocked an alternative agonist-evoked CB1R-mediated activation of the cytoskeleton-associated ROCK signalling pathway, which relied on the GAP43-mediated impairment of CB1R/Gq/11 protein coupling. GAP43 also abrogated CB1R-mediated ROCK activation in mouse hippocampal neurons, and this process led in turn to a blockade of cannabinoid-evoked neurite collapse. An NMR-based characterization of the CB1R-GAP43 interaction supported that GAP43 binds directly and specifically through multiple amino acid stretches to the C-terminal domain of the receptor. Taken together, our findings unveil a CB1R-Gq/11-ROCK signalling axis that is selectively impaired by GAP43 and may ultimately control neurite outgrowth.

Discovery of a selective and biologically active low-molecular weight antagonist of human interleukin-1β

Human interleukin-1β (hIL-1β) is a pro-inflammatory cytokine involved in many diseases. While hIL-1β directed antibodies have shown clinical benefit, an orally available low-molecular weight antagonist is still elusive, limiting the applications of hIL-1β-directed therapies. Here we describe the discovery of a low-molecular weight hIL-1β antagonist that blocks the interaction with the IL-1R1 receptor. Starting from a low affinity fragment-based screening hit 1, structure-based optimization resulted in a compound (S)-2 that binds and antagonizes hIL-1β with single-digit micromolar activity in biophysical, biochemical, and cellular assays. X-ray analysis reveals an allosteric mode of action that involves a hitherto unknown binding site in hIL-1β encompassing two loops involved in hIL-1R1/hIL-1β interactions. We show that residues of this binding site are part of a conformationally excited state of the mature cytokine. The compound antagonizes hIL-1β function in cells, including primary human fibroblasts, demonstrating the relevance of this discovery for future development of hIL-1β directed therapeutics.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Fragment-Based Drug Discovery by NMR. Where Are the Successes and Where can It Be Improved?

Over the last century, the definitions of pharmaceutical drug and drug discovery have changed considerably. Evolving from an almost exclusively serendipitous approach, drug discovery nowadays involves several distinct, yet sometimes interconnected stages aimed at obtaining molecules able to interact with a defined biomolecular target, and triggering a suitable biological response. At each of the stages, a wide range of techniques are typically employed to obtain the results required to move the project into the next stage. High Throughput Screening (HTS) and Fragment Based Drug Design (FBDD) are the two main approaches used to identify drug-like candidates in the early stages of drug discovery. Nuclear Magnetic Resonance (NMR) spectroscopy has many applications in FBDD and is used extensively in industry as well as in academia. In this manuscript, we discuss the paths of both successful and unsuccessful molecules where NMR had a crucial part in their development. We specifically focus on the techniques used and describe strengths and weaknesses of each stage by examining several case studies. More precisely, we examine the development history from the primary screening to the final lead optimisation of AZD3839 interacting with BACE-1, ABT-199 interacting with BCL2/XL and S64315 interacting with MCL-1. Based on these studies, we derive observations and conclusions regarding the FBDD process by NMR and discuss its potential improvements.

Fragment-to-Lead Medicinal Chemistry Publications in 2020

Fragment-based drug discovery (FBDD) continues to evolve and make an impact in the pharmaceutical sciences. We summarize successful fragment-to-lead studies that were published in 2020. Having systematically analyzed annual scientific outputs since 2015, we discuss trends and best practices in terms of fragment libraries, target proteins, screening technologies, hit-optimization strategies, and the properties of hit fragments and the leads resulting from them. As well as the tabulated Fragment-to-Lead (F2L) programs, our 2020 literature review identifies several trends and innovations that promise to further increase the success of FBDD. These include developing structurally novel screening fragments, improving fragment-screening technologies, using new computer-aided design and virtual screening approaches, and combining FBDD with other innovative drug-discovery technologies.