5 latest developments in Fragment Drug Discovery (FBDD)

Fragment-based drug discovery (FBDD) refers to screening small molecule compounds for target molecules, then optimizing and connecting these high-affinity fragments to create affinity ligands with high hit rates
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FBDD technology is the foundation of many drug discovery projects today.
In this article, we summarized 5 recent advances in the use of fragment-based screening technology in a series of target molecules and indications
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1.
Fragment cutting Fragment cutting is a combination of traditional FBDD technology and structure-based drug design
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This method allows researchers to design molecular fragments from smaller components and then join these fragments together for further evaluation, including emergency identification of potential drugs against the SARS-CoV-2 virus during Covid-19
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At that time, researchers used fragment tailoring to construct the main protease of the virus
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Researchers used computational methods to design molecular fragments, link them together, and bind to different positions of SARS-CoV-2-M at the same time, and then screened a library of nearly 200,000 fragments targeting the protease binding cavity, any combination Adjacent high-affinity fragments will be connected to generate the final new candidate molecule
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These molecules have drug-like properties and possible binding affinity.
The researchers evaluated the candidate list of a variety of candidate molecules through molecular dynamics simulations, of which 17 were found to form stable complexes with SARS-CoV-2-M
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It is worth noting that these novel drug candidates for COVID-19 cannot be developed through traditional high-temperature superconducting methods in the past
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2.
Screening by affinity mass spectrometry fragments.
G protein-coupled receptors (GPCRs) are ligands that bind to a site other than the main active site.
There are a series of potential therapeutic applications in a variety of diseases, including heart disease to cancer , And identifying negative allosteric modulators (NAMs) is particularly challenging.
NAMs can inhibit receptor activation
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Recently, a new method that combines affinity mass spectrometry (MS) with FBDD has been used to screen potential NAM fragment libraries, which can target the sodium-binding pockets of adenosine A receptors, which are involved in inflammation and heart disease.
A target for extensive exploration
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Compared with conventional surface plasmon resonance or NMR-based FBDD methods, by using affinity MS to enrich specific conjugates, the amount of target protein and fragment library compound mixture used can be reduced by 2 to 4 times, and the analysis speed can be increased by 2 To 3 times
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This method identified a new type of NAM characterized in that the azetidine moiety is believed to occupy the allosteric sodium binding site
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This discovery will provide NAM design with information on the sodium ions of Class A GPCRs and demonstrate the ability to combine affinity MS with FBDD to identify allosteric inhibitors of other GPCR targets
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3.
Fluorine-19 nuclear magnetic resonance spectroscopy.
Nuclear magnetic resonance spectroscopy is a mature FBDD technology.
The method is to measure the displacement of the quantum spectrum of the 15N-labeled target protein at the fragment ligand binding site
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The latest developments show that the technology has been extended to other target molecules
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In a study, fluorine-19NMR can be used to screen 14 different RNAs (a database containing 102 fragments), revealing the druggability of different sizes and secondary and tertiary RNA structures, including hairpin structures to Bacterial riboswitches have various structures, which can naturally bind low molecular weight metabolites with high affinity and specificity
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Fluorine-19-based detection has advantages over other NMR-based methods because the fluorine-19 spectrum shows a higher chemical shift dispersion, making it more sensitive in detecting weak binding activity
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The identified fragments can be easily further optimized through direct follow-up chemistry to increase binding affinity while still maintaining selectivity between different RNA targets
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4.
Fragment calculation protocol The calculation method is usually used before the experimental fragment screening, to design potential screening fragments (such as fragment tailoring methods) or to reduce the compound database to a more manageable collection
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These methods use molecular docking to simulate the binding of visualized fragments to different sites on the target protein
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To this end, researchers need to use X-ray crystallography methods to obtain the experimental structure of the target protein, or use a known binding agent to explore the related chemical structure
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However, based on the observation that certain ligand fragments tend to bind to conserved protein subbags of evolutionary unrelated proteins, researchers have developed a new virtual screening tool FRAGSITE for this purpose, which uses the similarity of unrelated target proteins.
Site-bound ligand fragment
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In experimental tests, FRAGSITE has a higher hit rate than other virtual screening tools, and identifies new molecules with different scaffolds and nanomolar affinities for the tested targets
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Another recent development is a computational protocol called High-throughput Supervised Molecular Dynamics (HT-SuMD)
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The HT-SuMD protocol allows researchers to use the 3D target structure and the fragment database to be screened to prepare, run and analyze thousands of simulations in a fully automated manner, and accelerate the sampling of combined events to a few seconds.
This is by far the largest completely based Fragment screening calculation of molecular dynamics
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5.
Fragment Phenotype Lead Discovery (FPLD) For a long time, it has been believed that the weak binding affinity of fragments used in FBDD will not be detected in cell-based phenotyping analysis, or that fragment databases with high enough concentration can be used to obtain high The hit rate will cause toxicity and inaccurate readings
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But recently, researchers have successfully used a library of selected fragments to achieve their goals in infectious disease models
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In a study, researchers screened 169 compound databases against a range of pathogens (Leish fever, Plasmodium falciparum, Neisseria, Mycobacterium, and Flavivirus), each containing 7 to 12 compounds
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The experimenter performed deconvolution in a separate assay for each pathogen and compared it with previous hits from HTS
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This proof-of-concept study did not observe non-specific inhibition and toxicity as expected, but found that phenotypic screening has brought a series of hit data that can be further explored
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In addition, the method can also be used more widely for other diseases that lack clear clinical goals, such as nervous system and cardiovascular diseases, and certain types of cancer.

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