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A Fragment-Based Approach to Boost Drug Discovery Productivity

The ability to identify clinically valuable fragments is key to accelerating drug discovery.

Drug discovery is expensive and time consuming. Productivity in drug discovery is tied to the ability to identify drug-like molecules that can be used to target clinically relevant pathways. For the last 20 to 30 years, Fragment-based drug discovery (FBDD) has emerged as a complementary approach to high-throughput screening (HTS) methods. FBDD is based on the theoretical concept of using small pieces of chemical fragments to bind to the active site of protein targets, as individual chemical functional groups can affect the binding energy between a drug and its target. I’m here. Furthermore, the fragments have a simpler structure, which reduces the likelihood of unwanted interactions from side functional groups that can complicate the actual binding affinity.

FBDD is also advantageous because fragment libraries sample a much larger chemical space than HTS and can generate regular hits for optimization. Importantly, hit rates from fragments can be used to assess whether biological targets, even more complex targets such as protein-DNA interactions, are potentially druggable. This article describes recent advances in the field of FBDD.

Validating hits from FBDD

Fragments have weaker affinities compared to HTS. The equilibrium dissociation constant measures the tendency of a bound drug/target complex to dissociate into free drug and target. For FBDD, this is ~1 mM to 100 µM compared to ~100 nM to 10 µM for the HTS method. Therefore, sensitive biophysical methods are needed to accurately measure the affinity between fragments and their targets. Common examples include surface plasmon resonance (SPR), thermal shift affinity capture, X-ray crystallography, and nuclear magnetic resonance (NMR).

X-ray crystallography is a powerful tool for obtaining high-resolution structures of proteins and complexes. The resulting X-ray structures can be used to understand the mechanisms by which inhibitors bind to the target’s active site and the formation of covalent bonds at the active site. It is routinely used to identify and validate fragment hits. Using this method requires crystallizing the fragments to obtain the binding mechanism at high resolution.

“When it comes to choosing a technique such as X-ray crystallography, NMR or SPR of FBDD, it is important to know something more important than binding or related. A major advantage of X-ray crystallography is direct visualization It is not necessary to infer this information, but it is important to question whether the binding is related. It provides differences in signal strength that researchers use as a proxy to measure how strongly they interact with their targets.” Professor Frank von DelftSenior Research Fellow at the University of Oxford.

“In my opinion, there are two main challenges when using X-ray crystallography for FBDD. Second, the need for computational tools powerful enough to rapidly and reliably analyze structural information in crystals. Nevertheless, I am optimistic about using X-ray crystallography for FBDD, simply because of its ability to provide a “rich” amount of information to guide fragment studies. adds von Delft.

according to Dr. Julian Oatesan assistant professor at the University of Vienna, said that while X-ray crystallography remains the most efficient method of 3D structure elucidation available, it is not a reliable screening method. Developing NMR methods to improve processes.

“NMR probes a larger chemical space because it does not require crystallization to define whether a fragment is a true positive/binder. It is also possible to obtain the structure of the complex by

NMR is a highly sensitive technique that can distinguish fragments with different binding affinities in the nM to mM range, with low false positive rates. This is accomplished by measuring changes in the NMR signal from either the fragment/ligand or target/protein. Mixtures of compounds can be used for screening, but signal overlap limits the number of compounds that can be identified. Various isotopes can be used in NMR, such as Fluorine 19 and Phosphorus 31. However, conventional NMR structure calculation methods are not productive and fail to provide timely information on drug discovery timelines.

In a study led by Orts, Torres et al. An NMR molecular replacement method that can reduce the time required to generate ligand-protein complex structures by using the published structure of the target protein and downgrading the observed nuclear Overhauser effect as a non-critical constraint. (NMR2) was developed. This method 2020 Resolving the Complex Between Three Derivatives of Fragments and the Protein Receptor PIN1, a Peptidyl-Prolyl Sith/Trance Isomerases, overexpressed in several cancers, recognize phosphoserine/threonine-proline motifs that contribute to tumor initiation and growth. Recentlythe same group adapted the NMR2 method to understand the binding model to bromodomains that recognize post-translational modifications of BRD4 and TRIM24, proteins also implicated in cancer.

“FBDD has improved access to the chemical realm from the very beginning of the project due to the simplicity and diversity of the fragments. So by starting with simple “blocks” we can cover the largest possible chemical space and narrow the search only where it makes sense. ”

Orts would like to apply his NMR2 method to other targets. Since KRAS does not crystallize well, X-ray crystallography is useless and causes major problems in this case. KRAS is also highly dynamic, with flexible regions (loops) playing an important role in its function. NMR is inherently better suited to study flexible receptors. We are elucidating his NMR2 structure of his KRAS in complex with fragments to accelerate drug design for this oncoprotein,” he adds Orts.

Kinetic Curvature: Assessing Small Molecule Kinetics and Affinity

Detection and characterization of binding events is facilitated by sensitive biophysical techniques. Surface plasmon resonance (SPR) is a core technique used in many pharmaceutical and biotech settings for this purpose, but conventional initial SPR screening of weak affinity compounds using a single fixed concentration injection is , can present a number of challenges. Download this application note and discover how OneStep® injections can help.

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connect the pieces

After fragment hits are found, fragments can grow into more powerful compounds. This strategy is called fragment growth. Another method of creating potent compounds is to utilize fragment binding when fragments have overlapping binding sites that can be determined by X-ray crystallography. This can also be facilitated by analyzing the binding mode of the fragment to the target’s active site using NMR and molecular docking. The most powerful approach is fragment linking, which connects two or more fragments to dramatically improve binding affinity. For example, linking two fragments with binding affinities in the mM range will generate compounds with affinities in the nM range. However, for this approach to work, targets typically have relatively large binding pockets for fragments to bind to various regions within the pocket. Extensive structural information is also important for understanding molecular interactions.

mycobacterium abscesus (Mab) is a rapidly growing species of non-tuberculous mycobacterium (NTM) and is a major threat to individuals with cystic fibrosis. Phosphoribosylaminoimidazole succinocarboxamide synthetase, or PurC, is an essential enzyme involved in: de novo Purine biosynthesis in bacteria. PurC is an attractive target for antimicrobial drug discovery because of its distinct structural differences from its human orthologue, his PAICS. Charoensutthivarakul et al. used Studying FBDD approaches such as fragment growth and fragment binding to discover new classes of 4-amino-6-(pyrazol-4-yl)pyrimidine-based inhibitors.

Screening the two fragment libraries identified 35 fragments as hits, 60% of which were found to bind to the adenosine triphosphate (ATP) site of Mab PurC by X-ray crystallography. Based on structural information, the authors utilized various functional group additions and deletions to improve binding affinity. Importantly, the authors used hit fragments 1 and 2 to integrate fragment growth and merging strategies, resulting in significantly improved binding affinities ranging from >300 uM to 50–150 nM. I have generated two compounds. This method highlights the strength of FBDD in accelerating the overall hit-to-lead progression in drug discovery.A similar strategy has recently hired by Smith et al.Discover synthetic inhibitor MRTX1719 to treat cancer MTAP delete.

“In this paper, we used both fragment growing and merging to develop potent inhibitors of PurC. We used the structural data from both of these screens to develop these inhibitors.” Dr. Anthony CoyneSenior Research Fellow at the University of Cambridge.

“Although fragment growing is the most common method of refinement, fragment merging has also been used in previous medicinal chemistry campaigns. Our work on PurC allowed us to develop robust crystals for X-ray crystallography, and we were fortunate enough to solve more than 30 strategically important structures in this project. have been able to develop high-affinity inhibitors based on structural biology across a wide range of different targets, including: RAD51-BRCA2, Murbu When TRMDThe interplay of medicinal chemistry and structural biology is key to all the projects above,” Coyne adds.

Advance

FBDD has the potential to improve drug discovery productivity, so that more drugs may be approved for clinical use and benefit patients. However, the fragments bind weakly to their targets, requiring continued advances in techniques such as X-ray crystallography and NMR to provide high-resolution structural information and analyze ligand-receptor interactions. . New chemistries for synthesizing, growing, merging, and connecting fragments also facilitate faster hit-to-read optimization. FBDD could also benefit from growing interest. artificial intelligenceusing large datasets to predict the key properties of fragments and their bioactivity, as well as creating virtual fragments, has the potential to accelerate drug discovery.