Fragment-Based Drug Discovery: Opportunities and Challenges in Pharmaceutical Chemistry

The identification and creation of new therapeutic compounds constitute one of the major difficulties in pharmaceutical chemistry. Conventional methods for drug discovery, especially high-throughput screening (HTS), encompass evaluating extensive collections of drug-like compounds against target proteins. Though HTS has greatly aided in discovering new chemical entities, this traditional approach is becoming increasingly constrained by rising development expenses, prolonged periods, and the challenges in targeting structurally complex proteins. In the last twenty years, fragment-based drug discovery (FBDD) has become a transformative approach in pharmaceutical chemistry, providing a complementary and frequently better option to conventional screening techniques. ^{[1, 2]} FBDD embodies a bottom-up strategy for drug development that starts with small, low-molecular-weight entities known as "fragments." In contrast to traditional HTS that usually examines extensive libraries of drug-like substances with molecular weights over 400 Da, FBDD employs molecular fragments that typically fall between 150 and 300 Da, following the "rule of three" guidelines. This essential difference in strategy offers multiple strategic benefits: fragments show enhanced binding efficiency (ligand efficiency), necessitate fewer compounds for screening because of improved exploration of chemical space, and allow for the discovery of novel pharmacophores that traditional HTS might miss. The theoretical basis of FBDD is founded on the idea that small molecular fragments, despite having weak individual binding affinities with protein targets, can effectively act as initial points for methodical development into strong lead compounds via rational medicinal chemistry. Starting with fragments that engage particular binding sites on target proteins allows medicinal chemists to steer further optimization by utilizing comprehensive structural data acquired from diverse biophysical techniques, which ensures that the transition from fragment to lead compound is intentional and systematic instead of accidental. The influence of FBDD on pharmaceutical chemistry and the development of clinical drugs has been significant and increasing. As of now, eight drugs identified through FBDD have gained FDA approval, and over 50 compounds derived from FBDD have moved into clinical development spanning various therapeutic fields such as oncology, infectious diseases, and neurology. Prominent instances comprise vemurafenib (BRAF blocker for melanoma), venetoclax (BCL-2 blocker for blood cancers), pexidartinib (CSF-1R blocker), erdafitinib (pan-FGFR blocker), and asciminib (ABL allosteric blocker for chronic myeloid leukemia). This review offers an in-depth analysis of fragment-based drug discovery, covering its historical evolution, theoretical foundations, screening and optimization techniques, applications in difficult target categories, and the incorporation of new computational and AI-driven methods.

Fig 1- Fragment-Based Drug Discovery Workflow: From fragment hit identification through iterative optimization cycles to lead compound development.

2. Historical Development and Theoretical Foundations

2.1 Origins of Fragment-Based Drug Discovery

The conceptual underpinnings of FBDD originate from the groundbreaking research carried out at Abbott Laboratories in the mid-1990s, where scientists created the "SAR by NMR" (structure-activity relationship via nuclear magnetic resonance) technique. This innovative method showed that NMR spectroscopy could successfully detect weak-binding fragments and facilitate their refinement via repeated cycles of chemical synthesis and biophysical evaluation. This innovation contested the prevailing belief that larger, drug-like entities were inherently better foundations for drug discovery. The theoretical foundation for initiating drug discovery with fragments instead of drug-like compounds is based on several fundamental principles. Fragment-based methods provide enhanced ligand efficiency—the proportion of binding affinity to molecular weight—relative to larger compounds discovered via HTS. This improved efficiency signifies that fragments engage with protein binding sites in simpler, more atom-efficient manners, offering clearer direction for future optimization. Exploring chemical space with fragments instead of pre-synthesized drug-like libraries enables a more efficient sampling of the extensive terrain of potential chemical structures. ^[3,4]

2.2 Theoretical Principles Underlying FBDD

The effectiveness of Fragment-Based Drug Discovery (FBDD) is based on several key principles from biochemistry and medicinal chemistry:

1. Binding Efficiency and Ligand Efficiency: Fragments typically show higher binding efficiency than drug-like molecules. Ligand efficiency (LE), calculated as LE = 1.37 × log (IC50) divided by the number of heavy atoms, measures how well each atom in a molecule contributes to binding. Fragments usually have LE values greater than 0.3, whereas drug-like molecules identified through high-throughput screening (HTS) often have values below 0.25. This higher efficiency means fragments are more effective binding units, making them excellent starting points for further development.

2. Exploration of Chemical Space: The total number of possible drug-like organic molecules is estimated to be over 10^60. Screening large libraries of pre-made compounds only covers a tiny portion of this vast chemical space. In contrast, fragments act as modular building blocks that can be systematically combined and expanded to explore areas of chemical space that are otherwise inaccessible. This strategy enables researchers to discover new chemical scaffolds and pharmacophores that may not be present in commercially available screening collections.

3. Structural Insights and Binding Site Analysis: Since fragments interact with protein binding sites through fewer and more focused interactions than larger molecules, the structural data obtained from their binding provides clearer understanding of key binding interactions and the shape of the binding pocket. X-ray crystallography of fragment-protein complexes often reveals precise binding modes and binding site geometry, which supports rational design and optimization in subsequent stages^{. [5,6]}

3. Fragment Screening Methodologies ^[7,8,9,10]

Fragment screening represents the critical first phase of FBDD campaigns, wherein small molecular fragments are tested for binding interactions with target proteins. Unlike HTS, which relies on functional or biochemical assays, fragment screening typically employs biophysical methods capable of detecting weak binding events that would be below the threshold of conventional functional assays.

3.1 Biophysical Screening Techniques

Nuclear Magnetic Resonance (NMR) Spectroscopy:

NMR spectroscopy represents one of the most widely utilized techniques for fragment screening and represents the methodology upon which the original SAR by NMR approach was founded. NMR-based fragment screening offers several distinct advantages: it is label-free, solution-based, and provides direct observation of molecular interactions. Multiple NMR methodologies have been successfully applied to fragment screening:

1. Ligand-Detected NMR Methods: These approaches monitor changes in NMR spectra of ligand nuclei upon binding to protein targets. Saturation transfer difference (STD) NMR, for example, relies on selective protein saturation followed by transfer of magnetization to bound ligands. Water-LOGSY (Water-Ligand Observed through Group Saturation) represents an alternative ligand-detected approach. Fluorine-19 NMR has emerged as particularly valuable for fragment screening, offering increased sensitivity and the ability to screen mixtures of samples without spectral overlap.
2. Protein-Detected NMR Methods: These methods monitor changes in protein NMR spectra upon fragment binding. Hetero-nuclear single quantum coherence (HSQC) spectroscopy, particularly when applied with cryogenically cooled NMR probes, enables detection of chemical shift perturbations induced by fragment binding. Target-detected NMR methods provide direct structural information on fragment binding modes and protein conformational changes accompanying ligand binding.

Advantages: NMR enables screening of fragment libraries of thousands of compounds within hours using automated high-throughput platforms equipped with Cryo-probes operating at field strengths of 500-800 MHz or higher. The method provides quantitative binding affinity data (Kd values) and structural information on binding mechanisms without requiring protein immobilization or chemical modification.

Limitations: NMR requires relatively high concentrations of both protein and fragments (typically micromolar to millimolar), which can be problematic for poorly soluble compounds or proteins available in limited quantities.

Surface Plasmon Resonance (SPR):

SPR is a real-time, label-free biophysical method that tracks variations in refractive index at the surface of a sensor chip as a result of molecule interactions. On the surface of the sensor chip, one binding partner—usually the protein target—is immobilised, and the other binding partner moves over the surface. The SPR signal rises in proportion to the bulk of the bound material as a result of binding events. SPR's benefits for fragment screening SPR provides FBDD applications with a number of benefits. The technique simply needs little amounts of protein (usually nanomoles) to prepare the sensor. Kinetic rate constants and equilibrium dissociation constants (Kd) are both provided by SPR. It has been shown that systematic SPR-based screening of fragment libraries against target panels generates high-efficiency results.

X-ray Crystallography:

Atomic-resolution, direct, three-dimensional structural information about fragment-protein complexes can be obtained by X-ray crystallography. Pre-formed protein crystals are usually soaked in fragment solutions for fragment screening by crystallography, after which data is gathered and the structure is ascertained. The throughput and accessibility of X-ray crystallographic fragment screening have significantly enhanced thanks to recent advancements like automated crystal screening at synchrotron facilities (such the X-Chem facility at Diamond Light Source). Benefits of X-ray crystallography include precise placement inside the binding site, caused conformational changes in both the ligand and the protein, and clear, high-resolution structural information on fragment binding mechanisms. For the purpose of directing further fragment optimisation, this structural knowledge is quite helpful. From months-long procedures to automated systems that can analyse hundreds of fragment-protein complexes, crystallographic screening has changed throughout time.

Limitations: X-ray crystallography requires well-diffracting protein crystals suitable for soaking experiments and access to synchrotron facilities for efficient data collection.

Thermal Shift Assays (TSA/FTSA):

Thermal shift assays, commonly known as differential scanning fluorimetry (DSF) or fluorescence thermal shift assay (FTSA), track the stabilisation of protein thermal stability following ligand binding. Protein samples, either with or without test chemicals, are heated gradually while the unfolding of the protein is seen by changes in the fluorescence of environment-sensitive dyes like SYPRO Orange. Increased thermal melting temperature (Tm) shifts are the result of compounds that stabilise the protein.

Benefits: TSA is a straightforward, reasonably priced screening technique that works with high-throughput automation and requires little amounts of protein. The technique doesn't require protein immobilisation or modification and can be used with a variety of target classes.

Limitations: TSA lacks quantitative affinity information and only offers a binary readout of binding (stabilization/no stabilisation). Measurable thermal stabilisation is not the outcome of every protein-ligand interaction.

Microscale Thermophoresis (MST):

MST is a solution-based biophysical method that uses solutions of tiny temperature gradients produced by concentrated infrared lasers to quantify changes in molecular mobility. Temperature gradients created by MST are applied to labelled proteins, and variations in fluorescence intensity indicate modifications in thermophoretic mobility as a result of ligand binding. Benefits of MST include its solution-based nature, which eliminates the need for chemical modification or protein immobilisation (when employing intrinsic protein fluorescence). The methodology works with proteins that are prone to aggregation or have poor solubility, which are issues with conventional methods. Quantitative affinity determination is provided by MST.

Limitations: MST's applicability to fluorescent proteins is limited because it usually requires protein fluorescence labelling or depends on natural tryptophan fluorescence.

3.2 Fragment Library Design and Composition

The success of FBDD campaigns is significantly influenced by the layout and makeup of fragment screening libraries. 500–2500 distinct compounds with substantial structural diversity that meet the rule-of-three criteria are found in successful fragment libraries. One of the guiding concepts of library design is structural diversity, which states that fragment libraries are designed to maximise the investigation of a variety of chemical spaces, such as linear chains, heterocyclic scaffolds, aromatic rings, and saturated ring complexes [11]. While pharmacophore representation states that modern fragment libraries incorporate representation of diverse pharmacophoric groups such as hydrogen bond donors and acceptors, aromatic ring systems, and basic and acidic functionalities, diversity-oriented synthesis approaches produce libraries with a variety of topologies and functional group compositions. The likelihood of finding hits against various target protein binding sites is increased by this pharmacophoric variety.

4. Fragment Optimization Strategies ^[12,13,14]

The next task is to systematically develop these weak-binding fragments into strong lead compounds with advantageous drug-like characteristics after fragment hits have been identified through screening campaigns. Perhaps the most difficult part of FBDD is fragment optimisation, which calls for a close combination of molecular biology knowledge, medicinal chemistry inventiveness, and structural understanding.

4.1 Fragment Growing

The most straightforward and widely used optimisation technique is fragment growing. This approach keeps a verified fragment hit inside the binding pocket while methodically adding chemical substituents to take advantage of extra interactions with the residues and pockets of protein binding sites.

Methodology: Medicinal chemists determine accessible "vectors" for chemical growth—directions within the binding pocket where extra molecular weight can be added without altering the initial fragment binding interactions—after structurally characterising a fragment-protein complex, usually by X-ray crystallography or NMR. Gradual increases in binding affinity are achieved by methodically modifying these vectors through recurrent synthesis cycles and biophysical/biochemical testing.

Benefits: Direct structural guidance from fragment binding information allows for precise, atom-by-atom molecular structure optimisation through fragment growth. This approach typically results in consistent, predictable improvements in binding affinity with each chemical modification cycle. The method works with a variety of target classes and binding site shapes.

Challenges: Growing fragments can be resource-intensive, involving several synthesis and test cycles.

4.2 Fragment Linking

A more ambitious optimisation technique known as "fragment linking" involves covalently joining two non-competitive fragments—fragments that bind at different sub-pockets inside the target binding site—using chemical linker groups. By simultaneously taking advantage of several binding site interactions, this strategy has the potential to significantly increase potency.

Methodology: In linking approaches, the binding mechanisms of two validated fragment hits are first described independently. The spatial distance between the two fragment binding locations is then used to guide the linker design process. To join the two fragments while preserving their initial binding orientations, the linker needs to have the right length and flexible in its conformation. Chemical spacers have been used as linkers with success, ranging from straightforward chains to stiff scaffolds.

Benefits: Compared to merely expanding individual pieces, fragment linking can result in notable increases in binding affinity. Linking frequently produces new chemical scaffolds that are difficult to obtain through other synthetic methods.

Problems: Of the fragment optimisation techniques, linking is the most difficult. Finding linkers with the ideal length, flexibility, and chemical characteristics calls for both synthetic knowledge and advanced computational chemistry.

4.3 Fragment Merging

Combining two or more fragment hits that attach to neighbouring or overlapping portions of the target binding site is known as fragment merging. This method replaces several pharmacophoric elements with a single core structure by combining the common pharmacophoric elements into a single molecular scaffold. This optimisation method is especially useful for substituting more advantageous scaffolds for non-drug-like core structures while preserving pharmacophoric characteristics necessary for target binding.

Methodology: The overlapping binding interactions are detected after several fragment hits and their binding modalities have been characterised. The inventiveness of medicinal chemistry is then used to create molecular scaffolds that preserve important binding interactions while getting rid of unnecessary functionality. New chemical entities with enhanced drug-like qualities are frequently produced as a result of mergers.

Benefits: Compared to linking techniques, fragment merging can significantly lower molecular weight and complexity while preserving or improving binding affinity. Challenges: Deep chemical intuition and knowledge of structure-activity connections are necessary for designing suitable merging scaffolds.                              

Fig 2- Detailed illustration of the three main optimization approaches: growing, linking, and merging, showing molecular structures and binding site interactions.

4.4 Structure-Activity Relationship (SAR) by Catalog and Nearest Neighbor Approaches

Medicinal chemistry commonly uses SAR by catalogue approaches, which go beyond the three main optimisation strategies (growing, linking, and merging). These methods obtain commercially available compounds that are structurally similar to validated fragment hits (also known as "nearest neighbours") and quickly assess their activity. With this method, SAR for the fragment hit chemotype is quickly established. Unexpected SAR, highly advantageous chemical substitutions, and suggestions for synthetic elaboration pathways can all be found in nearest neighbour compounds.

4.5 Computational Approaches to Fragment Optimization ^[15]

In fragment optimisation, computational techniques have grown in importance, supporting and expediting experimental medicinal chemistry initiatives:

Molecular Docking and Scoring: Prior to production, synthetic candidates can be virtually ranked using computational docking techniques, which anticipate how suggested molecules will interact to protein targets. Docking helps medicinal chemists make judgements about chemical changes by visualising predicted protein-ligand interactions in three dimensions. Protein flexibility, water-mediated ligand interactions, and induced-fit effects that could affect ligand binding are all described by molecular dynamics (MD) simulations. Understanding allosteric effects and conformational changes that accompany ligand binding has been made easier with the use of MD studies.

Quantitative Structure-Activity Relationship (QSAR) Modelling: QSAR techniques provide mathematical models that link biological activity and molecular structure, making it possible to predict activity for compounds that haven't been synthesised yet. The prediction capability and application of QSAR modelling have been significantly improved by machine learning and deep learning techniques.

Artificial Intelligence and Machine Learning: Machine learning and artificial intelligence techniques are rapidly being used in modern computing systems. Large databases of structure-activity data can be used to train deep learning neural networks, which can then predict binding affinities, optimise molecular characteristics, and find viable synthetic candidates.

5. Successful Applications and Clinical Examples ^[16,17,18]

The clinical validation of FBDD has been decisively demonstrated through the FDA approval of multiple drugs discovered through fragment-based methodologies and the advancement of numerous compounds into clinical development.

5.1 FDA-Approved FBDD-Derived Drugs

• Vemurafenib (PLX4032): One of the most well-known instances of effective FBDD is vemurafenib. Plexikon (now a part of Daiichi Sankyo) ran a fragment-based approach that led to the discovery of this BRAF kinase inhibitor for melanoma. Vemurafenib (IC50 <10 nM) was produced by methodically developing a fragment hit with an affinity of 50 µM across several optimisation cycles. It took only about 6 years from project inception to regulatory approval, which is significantly less time than is usually needed for pharmaceutical development. Vemurafenib is now a standard-of-care treatment for BRAF-mutant melanoma after receiving FDA clearance in 2011.
• Venetoclax (ABT-199): Venetoclax is a prime example of FBDD's ability to successfully target protein-protein interactions, particularly the BCL-2 protein complex. Weak-binding fragments to BCL-2 were found by early fragment screening campaigns using SAR by NMR techniques developed at Abbott Laboratories. Venetoclax, a selective BCL-2 inhibitor with picomolar binding affinity, was produced by further fragment optimisation using growing and linking techniques. A key component of lymphoma treatments, venetoclax was approved by the FDA in 2016 for the treatment of chronic lymphocytic leukaemia.
• Pexidartinib (PLX3397): Developed using fragment-based methods, this inhibitor of the colony-stimulating factor-1 receptor (CSF-1R) was approved by the FDA in 2019 for the treatment of tenosynovial giant cell tumour.
  Astex and Johnson & Johnson collaborated to find erdafitinib (Balversa), a pan-FGFR (fibroblast growth factor receptor) inhibitor that was approved by the FDA in 2019 for the treatment of urothelial cancer with FGFR mutations.
• Asciminib (ABL001): FDA approved this allosteric ABL tyrosine kinase inhibitor for chronic myeloid leukaemia in 2021 after it was found using fragment-based screening and NMR-guided optimisation. Asciminib is an example of how FBDD techniques can effectively target allosteric sites.

5.2 Clinical Candidates and Development Pipeline

With ongoing Phase I, II, and III trials assessing therapeutic efficacy across a variety of diseases, including oncology, infectious illness, inflammation, neurology, and metabolic disorders, more than fifty FBDD-derived drugs have reached clinical development. This sizable clinical pipeline shows the FBDD approach's wide applicability to difficult pharmacological targets and validates it.

5.3 FBDD Applications in Challenging Target Classes

Protein-Protein Interactions (PPIs):

Targets for protein-protein interactions are especially difficult to find. Historically, PPIs have defied small-molecule targeting due to their broad, flat binding surfaces. Because it can detect tiny molecule fragments attaching to surface pockets and "hotspots" on PPI interfaces, FBDD has been very useful for the discovery of PPI inhibitors. The interaction can be effectively disrupted by extending fragment impacts to span the interface. IAP (inhibitor of apoptosis proteins), p53 pathway connections, and BCL-2 family protein interactions are notable examples of effective applications.

Allosteric Modulation:

Finding allosteric modulators—compounds that bind to secondary locations different from the original orthosteric binding site—has proven very beneficial for FBDD. Improved selectivity (since allosteric sites frequently show more sequence diversity across protein families), tunable pharmacodynamic effects (positive or negative modulation instead of total inhibition), and the ability to target previously "undruggable" orthosteric sites are some potential benefits of allosteric modulators. Allosteric hits against a variety of receptors and enzymes have been effectively found by fragment screening and developed into lead compounds and clinical candidates.

Fig 3- Visual representation of how FBDD addresses PPIs by identifying fragments binding to interface hotspots