Discovery of Novel Inhibitors of Uridine Diphosphate-N-Acetylenolpyruvylglucosamine Reductase (MurB) from Pseudomonas aeruginosa, an Opportunistic Infectious Agent Causing Death in Cystic Fibrosis Patients.

Pseudomonas aeruginosa is of major concern for cystic fibrosis patients where this infection can be fatal. With the emergence of drug-resistant strains, there is an urgent need to develop novel antibiotics against P. aeruginosa. MurB is a promising target for novel antibiotic development as it is involved in the cell wall biosynthesis. MurB has been shown to be essential in P. aeruginosa, and importantly, no MurB homologue exists in eukaryotic cells. A fragment-based drug discovery approach was used to target Pa MurB. This led to the identification of a number of fragments, which were shown to bind to MurB. One fragment, a phenylpyrazole scaffold, was shown by ITC to bind with an affinity of Kd = 2.88 mM (LE 0.23). Using a structure guided approach, different substitutions were synthesized and the initial fragment was optimized to obtain a small molecule with Kd = 3.57 µM (LE 0.35).

Integrated human/SARS-CoV-2 metabolic models present novel treatment strategies against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic caused by the new coronavirus (SARS-CoV-2) is currently responsible for more than 3 million deaths in 219 countries across the world and with more than 140 million cases. The absence of FDA-approved drugs against SARS-CoV-2 has highlighted an urgent need to design new drugs. We developed an integrated model of the human cell and SARS-CoV-2 to provide insight into the virus' pathogenic mechanism and support current therapeutic strategies. We show the biochemical reactions required for the growth and general maintenance of the human cell, first, in its healthy state. We then demonstrate how the entry of SARS-CoV-2 into the human cell causes biochemical and structural changes, leading to a change of cell functions or cell death. A new computational method that predicts 20 unique reactions as drug targets from our models and provides a platform for future studies on viral entry inhibition, immune regulation, and drug optimisation strategies. The model is available in BioModels (https://www.ebi.ac.uk/biomodels/MODEL2007210001) and the software tool, findCPcli, that implements the computational method is available at https://github.com/findCP/findCPcli.

Structural insights into Escherichia coli phosphopantothenoylcysteine synthetase by native ion mobility-mass spectrometry.

CoaBC, part of the vital coenzyme A biosynthetic pathway in bacteria, has recently been validated as a promising antimicrobial target. In this work, we employed native ion mobility-mass spectrometry to gain structural insights into the phosphopantothenoylcysteine synthetase domain of E. coli CoaBC. Moreover, native mass spectrometry was validated as a screening tool to identify novel inhibitors of this enzyme, highlighting the utility and versatility of this technique both for structural biology and for drug discovery.

Identification of new allosteric sites and modulators of AChE through computational and experimental tools.

Allosteric sites on proteins are targeted for designing more selective inhibitors of enzyme activity and to discover new functions. Acetylcholinesterase (AChE), which is most widely known for the hydrolysis of the neurotransmitter acetylcholine, has a peripheral allosteric subsite responsible for amyloidosis in Alzheimer's disease through interaction with amyloid ß-peptide. However, AChE plays other non-hydrolytic functions. Here, we identify and characterise using computational tools two new allosteric sites in AChE, which have allowed us to identify allosteric inhibitors by virtual screening guided by structure-based and fragment hotspot strategies. The identified compounds were also screened for in vitro inhibition of AChE and three were observed to be active. Further experimental (kinetic) and computational (molecular dynamics) studies have been performed to verify the allosteric activity. These new compounds may be valuable pharmacological tools in the study of non-cholinergic functions of AChE.

Pantothenic acid biosynthesis in the parasite Toxoplasma gondii: a target for chemotherapy.

Toxoplasma gondii is a major food pathogen and neglected parasitic infection that causes eye disease, birth defects, and fetal abortion and plays a role as an opportunistic infection in AIDS. In this study, we investigated pantothenic acid (vitamin B5) biosynthesis in T. gondii. Genes encoding the full repertoire of enzymes for pantothenate synthesis and subsequent metabolism to coenzyme A were identified and are expressed in T. gondii. A panel of inhibitors developed to target Mycobacterium tuberculosis pantothenate synthetase were tested and found to exhibit a range of values for inhibition of T. gondii growth. Two inhibitors exhibited lower effective concentrations than the currently used toxoplasmosis drug pyrimethamine. The inhibition was specific for the pantothenate pathway, as the effect of the pantothenate synthetase inhibitors was abrogated by supplementation with pantothenate. Hence, T. gondii encodes and expresses the enzymes for pantothenate synthesis, and this pathway is essential for parasite growth. These promising findings increase our understanding of growth and metabolism in this important parasite and highlight pantothenate synthetase as a new drug target.

Structural biology in fragment-based drug design.

Fragment-based ligand screening is now established as an emerging paradigm for drug discovery. Here we examine the recent literature looking at how structural biology has been used in a variety of successful fragment-screening applications. We argue that the determination of experimental binding modes has proved to be one of the mainstays of successful fragment-based approaches and that this reflects the difficulty in optimising a fragment to a lead molecule in the absence of structural information. We focus on antimicrobial research where fragment-based drug discovery allows control of the physical properties of the emerging lead molecule.

Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery.

Impressive progress in genome sequencing, protein expression and high-throughput crystallography and NMR has radically transformed the opportunities to use protein three-dimensional structures to accelerate drug discovery, but the quantity and complexity of the data have ensured a central place for informatics. Structural biology and bioinformatics have assisted in lead optimization and target identification where they have well established roles; they can now contribute to lead discovery, exploiting high-throughput methods of structure determination that provide powerful approaches to screening of fragment binding.

Organisation of the pantothenate (vitamin B5) biosynthesis pathway in higher plants.

Pantothenate (vitamin B5) is the precursor for the biosynthesis of the phosphopantetheine moiety of coenzyme A and acyl carrier protein, and is synthesised in Escherichia coli by four enzymic reactions. Ketopantoate hydroxymethyltransferase (KPHMT) and pantothenate synthetase (PtS) catalyse the first and last steps, respectively. Two genes encoding KPHMT and one for PtS were identified in the Arabidopsis thaliana genome, and cDNAs for all three genes were amplified by PCR. The cDNAs were able to complement their respective E. coli auxotrophs, demonstrating that they encoded functional enzymes. Subcellular localisation of the proteins was investigated using green fluorescent protein (GFP) fusions and confocal microscopy. The two KPHMT-GFP fusion proteins were targeted exclusively to mitochondria, whereas PtS-GFP was found in the cytosol. This implies that there must be transporters for pathway intermediates. KPHMT enzyme activity could be measured in purified mitochondria from both pea leaves and Arabidopsis suspension cultures. We investigated whether Arabidopsis encoded homologues of the remaining two pantothenate biosynthesis enzymes from E. coli, l-aspartate-alpha-decarboxylase (ADC) and ketopantoate reductase (KPR). No homologue of ADC could be identified using either conventional blast or searches with the program fugue in which the structure of the E. coli ADC was compared to all the annotated proteins in Arabidopsis. ADC also appears to be absent from the genome of the yeast, Saccharomyces cerevisiae, by the same criteria. In contrast, a putative Arabidopsis oxidoreductase with some similarity to KPR was identified with fugue.

Discrete restraint-based protein modeling and the Calpha-trace problem.

We present a novel de novo method to generate protein models from sparse, discretized restraints on the conformation of the main chain and side chain atoms. We focus on Calpha-trace generation, the problem of constructing an accurate and complete model from approximate knowledge of the positions of the Calpha atoms and, in some cases, the side chain centroids. Spatial restraints on the Calpha atoms and side chain centroids are supplemented by constraints on main chain geometry, phi/xi angles, rotameric side chain conformations, and inter-atomic separations derived from analyses of known protein structures. A novel conformational search algorithm, combining features of tree-search and genetic algorithms, generates models consistent with these restraints by propensity-weighted dihedral angle sampling. Models with ideal geometry, good phi/xi angles, and no inter-atomic overlaps are produced with 0.8 A main chain and, with side chain centroid restraints, 1.0 A all-atom root-mean-square deviation (RMSD) from the crystal structure over a diverse set of target proteins. The mean model derived from 50 independently generated models is closer to the crystal structure than any individual model, with 0.5 A main chain RMSD under only Calpha restraints and 0.7 A all-atom RMSD under both Calpha and centroid restraints. The method is insensitive to randomly distributed errors of up to 4 A in the Calpha restraints. The conformational search algorithm is efficient, with computational cost increasing linearly with protein size. Issues relating to decoy set generation, experimental structure determination, efficiency of conformational sampling, and homology modeling are discussed.