Popular Reports / Drug Discovery

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This report is written by MaltSci based on the latest literature and research findings

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How does fragment-based drug discovery work?

Abstract

Fragment-based drug discovery (FBDD) has become a transformative strategy in the pharmaceutical industry, addressing the limitations of traditional drug discovery methods such as high-throughput screening (HTS). This approach focuses on identifying small chemical fragments that bind weakly to biological targets, primarily proteins, enabling researchers to explore a vast chemical space with relatively low-molecular-weight compounds, typically under 300 Da. The significance of FBDD is highlighted by its ability to generate high hit rates and efficiently optimize lead compounds into clinically relevant drugs. With at least seven FDA-approved drugs derived from FBDD, this methodology has successfully targeted previously 'undruggable' proteins, expanding therapeutic options for various diseases, including cancer and infectious diseases. The iterative processes of fragment growing, merging, and linking, bolstered by advancements in computational techniques and artificial intelligence, have significantly improved the accuracy and efficiency of fragment optimization. However, challenges remain, particularly in the need for sophisticated biophysical methods to validate weak binding affinities and a comprehensive understanding of structure-activity relationships (SAR) to transform fragments into high-affinity ligands. This review provides a comprehensive overview of FBDD, detailing its principles, screening techniques, optimization strategies, real-world applications, challenges, and future perspectives. Through this exploration, we aim to illuminate how FBDD works, its current status in drug discovery, and its future potential to revolutionize the development of new therapeutics.

Outline

This report will discuss the following questions.

• 1 Introduction
• 2 Principles of Fragment-Based Drug Discovery
  • 2.1 Definition and Overview of FBDD
  • 2.2 Comparison with Traditional Drug Discovery Methods
• 3 Fragment Screening Techniques
  • 3.1 Biophysical Methods
  • 3.2 Structural Biology Techniques
  • 3.3 Computational Approaches
• 4 Fragment Optimization Strategies
  • 4.1 Fragment Growing
  • 4.2 Fragment Merging
  • 4.3 Structure-Activity Relationship (SAR) Studies
• 5 Applications and Case Studies
  • 5.1 Successful Drug Candidates Developed via FBDD
  • 5.2 Challenges and Limitations of FBDD
• 6 Future Perspectives in FBDD
  • 6.1 Emerging Technologies
  • 6.2 Integration with Other Drug Discovery Approaches
• 7 Conclusion

1 Introduction

Fragment-based drug discovery (FBDD) has emerged as a transformative strategy in the pharmaceutical industry, addressing the limitations of traditional drug discovery methods such as high-throughput screening (HTS). The core principle of FBDD involves the identification of small chemical fragments that can bind weakly to biological targets, primarily proteins. This approach allows researchers to explore a vast chemical space with a relatively small number of low-molecular-weight compounds, typically under 300 Da. The significance of FBDD lies not only in its ability to generate high hit rates but also in its efficiency in optimizing lead compounds into clinically relevant drugs [1].

The importance of FBDD is underscored by its success in targeting previously "undruggable" proteins, thereby expanding the repertoire of therapeutic options available for various diseases, including cancer and infectious diseases [2]. With at least seven FDA-approved drugs derived from FBDD, this methodology has demonstrated its capacity to overcome the challenges associated with traditional drug discovery paradigms [1]. Moreover, the iterative process of fragment growing, merging, and linking has been enhanced by advancements in computational techniques and artificial intelligence, which have significantly improved the accuracy and efficiency of fragment optimization [3].

Despite its advantages, FBDD is not without challenges. The weak binding affinities of initial fragment hits necessitate sophisticated biophysical methods for effective screening and validation [4]. Additionally, the transformation of these fragments into high-affinity ligands requires a deep understanding of structure-activity relationships (SAR) and innovative synthetic strategies [5]. Thus, while FBDD presents a promising avenue for drug discovery, it also requires a careful integration of various methodologies to maximize its potential.

This review aims to provide a comprehensive overview of FBDD by organizing the content into several key sections. First, we will delve into the principles of FBDD, including its definition and a comparison with traditional drug discovery methods. Following this, we will explore various fragment screening techniques, highlighting biophysical methods, structural biology approaches, and computational tools. The subsequent section will focus on fragment optimization strategies, detailing the processes of fragment growing, merging, and SAR studies. We will then examine real-world applications and case studies that illustrate the success of FBDD, while also addressing the challenges and limitations inherent to this approach. Finally, we will discuss future perspectives in FBDD, including emerging technologies and the potential for integration with other drug discovery methodologies.

Through this exploration, we aim to illuminate how FBDD works, its current status in the field of drug discovery, and its future potential to revolutionize the development of new therapeutics. By synthesizing recent advancements and highlighting key success stories, this review will serve as a valuable resource for researchers and practitioners seeking to understand and leverage the capabilities of fragment-based drug discovery in their own work.

2 Principles of Fragment-Based Drug Discovery

2.1 Definition and Overview of FBDD

Fragment-Based Drug Discovery (FBDD) is a strategic approach utilized in the drug discovery process, which focuses on identifying small molecular fragments as initial starting points for developing new therapeutic agents. The fundamental principle of FBDD lies in its ability to screen low-molecular-weight compounds, typically less than 300 Da, against biological targets. This method contrasts with traditional high-throughput screening (HTS) approaches, which often involve larger, more complex molecules.

FBDD operates on several core principles:

1. Fragment Screening: In FBDD, libraries composed of small fragments are screened against specific protein targets. These fragments, although binding with relatively low affinity, can establish efficient and high-quality interactions with the target protein's architecture. The binding of these fragments is characterized by overcoming a significant entropy barrier, which allows for precise identification of binding sites on the protein (Price et al. 2017) [6].

2. Biophysical Techniques: Various biophysical methods are employed to screen fragments, with X-ray crystallography being one of the most sensitive and reliable techniques. This method not only helps in detecting the binding of fragments to their targets but also provides detailed structural information about the protein-fragment complexes at an atomic level. Other techniques include nuclear magnetic resonance (NMR) spectroscopy, which aids in understanding the binding modes and optimizing fragment interactions (Kashyap et al. 2018) [7].

3. Hit-to-Lead Process: After identifying promising fragment hits, a crucial step in FBDD is the hit-to-lead process. This involves optimizing the identified fragments to enhance their binding affinity and pharmacological properties. The fragments can be elaborated through various strategies, including fragment growing, merging, and linking, to develop more potent lead compounds that exhibit higher efficacy against the target (Khedkar et al. 2025) [1].

4. Chemical Space Exploration: One of the significant advantages of FBDD is its ability to explore a broader chemical space compared to traditional methods. By using small fragments, researchers can identify diverse chemical scaffolds that may lead to novel drug candidates. This approach allows for a systematic exploration of chemical libraries, facilitating the discovery of compounds that can effectively interact with previously "undruggable" targets (Li et al. 2021) [8].

5. Iterative Optimization: FBDD is inherently iterative, as it involves repeated cycles of screening, binding mode analysis, and optimization. This iterative process allows chemists to refine the fragments progressively, enhancing their properties and ultimately leading to the development of viable drug candidates (Ferreira et al. 2017) [9].

Overall, FBDD represents a logical and efficient framework for lead discovery and optimization in medicinal chemistry. Its integration of structural biology and biophysical techniques provides a robust methodology for transforming small fragment hits into effective therapeutic agents, contributing significantly to the advancement of drug discovery across various therapeutic areas (de Kloe et al. 2009) [10].

2.2 Comparison with Traditional Drug Discovery Methods

Fragment-Based Drug Discovery (FBDD) is a strategic approach in drug discovery that has gained prominence due to its efficiency in identifying and developing new therapeutic agents. The fundamental principle of FBDD involves the utilization of small molecular fragments, typically with a molecular weight of less than 300 Da, as starting points for drug design. This method contrasts sharply with traditional drug discovery approaches, which often rely on larger, more complex compounds.

The FBDD process typically begins with the screening of libraries containing a limited number of low molecular weight fragments, which are designed to bind weakly to target proteins. This weak binding is advantageous as it allows for the exploration of a broader chemical space compared to the larger libraries used in traditional high-throughput screening (HTS) methods. In FBDD, fragments that exhibit binding to the target can be identified using various biophysical techniques, such as Nuclear Magnetic Resonance (NMR), X-ray crystallography, and surface plasmon resonance (SPR) [11][12].

Once promising fragments are identified, they undergo a process of optimization through strategies such as fragment growing, merging, and linking. Growing involves adding chemical moieties to the fragment to enhance binding affinity, while merging combines two or more fragments to create a more potent compound. Linking connects different fragments through a chemical linker to form a larger, more complex molecule that retains the desirable binding characteristics [3][5].

FBDD offers several advantages over traditional methods. It achieves higher hit rates and reduced screening costs, which leads to faster development timelines for drug candidates. Moreover, FBDD is particularly effective in targeting previously "undruggable" proteins, providing a pathway to develop drugs for complex diseases [1][10]. The approach has been validated by the successful progression of numerous fragment-derived compounds into clinical trials, with at least seven FDA-approved drugs stemming from this methodology, such as capivasertib [1].

In summary, FBDD represents a paradigm shift in drug discovery by focusing on small, efficient fragments that can be systematically optimized into potent therapeutic agents. This approach not only enhances the discovery of new drugs but also facilitates the exploration of novel targets that were previously considered difficult to drug, thus expanding the horizons of medicinal chemistry and therapeutic development [3][13].

3 Fragment Screening Techniques

3.1 Biophysical Methods

Fragment-based drug discovery (FBDD) is a sophisticated approach utilized in the identification of low molecular weight chemical starting points for drug discovery. This methodology has gained traction in both academic and industrial settings over the past two decades, proving effective for a range of challenging drug targets, including those related to cancer and neglected infectious diseases. Central to FBDD is the use of biophysical techniques to screen small libraries of compounds, typically consisting of 1000-2000 fragments, each with a molecular weight around 300 Da[4].

The screening process in FBDD relies on the interaction between fragments and target proteins, which usually occurs with relatively low affinity. This necessitates the employment of highly sensitive biophysical methods to detect such weak interactions. Among the various techniques available, X-ray crystallography stands out as one of the most sensitive and reliable methods for fragment screening. It provides detailed structural information about the protein-fragment complex at the atomic level, allowing for the identification of binding hotspots on proteins. This information is invaluable for subsequent drug design efforts[6].

Other notable biophysical methods include nuclear magnetic resonance (NMR), surface plasmon resonance (SPR), and isothermal titration calorimetry (ITC). NMR is particularly useful for protein-observed fragment screening, while SPR offers a label-free detection format that is advantageous for studying biomolecular interactions. The sensitivity of these techniques enables researchers to validate and characterize fragment hits, which is crucial for progressing from initial fragment identification to lead optimization[14].

Fragment-based drug discovery begins with the identification of low molecular weight fragments that exhibit weak binding to the target of interest. These fragments are then subjected to various biophysical screening techniques to identify those that form high-quality interactions with the target. The subsequent optimization of these fragments leads to the development of high-affinity ligands. This process often involves fragment growing, merging, or linking strategies to enhance the binding affinity and specificity of the lead compounds[5].

Despite the advantages of FBDD, there are inherent challenges, including the low throughput of experimental methods and the high costs associated with biophysical analyses. However, advancements in computational methods have complemented experimental approaches, enabling the design of fragment libraries and facilitating virtual fragment screening. This integration of computational techniques allows for a more extensive exploration of chemical space, thereby increasing the likelihood of discovering potent inhibitors for challenging therapeutic targets[11].

In summary, fragment-based drug discovery employs a variety of biophysical methods to screen low molecular weight fragments against target proteins, facilitating the identification and optimization of lead compounds. This approach, characterized by its sensitivity and ability to provide detailed structural insights, has established itself as a powerful strategy in the field of drug discovery[4][15][16].

3.2 Structural Biology Techniques

Fragment-based drug discovery (FBDD) is a sophisticated approach that focuses on identifying small, low-molecular-weight compounds, known as fragments, which bind weakly to biological targets. This methodology has gained traction as a powerful alternative to traditional high-throughput screening (HTS) methods, allowing for the efficient exploration of chemical space and the identification of lead compounds. The core principles of FBDD involve the systematic screening of fragment libraries, which typically consist of 1000-2000 compounds with a molecular weight of around 300 Da[4].

Fragment screening techniques utilize various biophysical methods to detect weak interactions between fragments and target proteins. Common techniques include nuclear magnetic resonance (NMR), X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry, and isothermal calorimetry. These methods enable the precise identification of fragment binding sites and the assessment of binding affinities, which are crucial for hit validation and subsequent optimization[17].

In FBDD, the initial identification of fragments is followed by a process known as fragment evolution, where the weakly binding fragments are elaborated into more potent inhibitors through three primary strategies: growing, merging, and linking. The growing strategy involves expanding the size of the fragment to enhance binding affinity, while merging combines two or more fragments to form a larger, more complex molecule. Linking connects two or more fragments via a linker to create a compound with improved binding characteristics[3].

Structural biology techniques play a pivotal role in FBDD by providing detailed insights into the binding interactions between fragments and their targets. For instance, X-ray crystallography can reveal the three-dimensional structure of the fragment-target complex, allowing for informed modifications to the fragment structure to improve potency and selectivity. Additionally, NMR can be employed to monitor conformational changes and binding dynamics, further guiding the optimization process[5].

The integration of computational techniques also enhances FBDD by facilitating virtual screening and molecular docking studies, which predict fragment binding affinities and guide the design of new compounds[18]. This combination of structural biology and computational methods enables a more rational approach to drug design, significantly improving the efficiency of the drug discovery process[19].

In summary, FBDD operates through a systematic approach that combines fragment screening with structural biology techniques to identify and optimize small-molecule inhibitors. The ability to explore vast chemical spaces efficiently, along with the strategic evolution of fragments into lead compounds, underscores the significance of FBDD in modern drug discovery efforts.

3.3 Computational Approaches

Fragment-based drug discovery (FBDD) is a sophisticated methodology that focuses on identifying small molecule hits that can be further developed into potent drug candidates. This approach capitalizes on the use of low molecular weight fragments, which typically exhibit weak binding affinities to biological targets. The process involves several key stages, including fragment screening techniques and computational approaches that enhance the efficiency and success of drug discovery efforts.

Fragment screening techniques are essential for identifying fragments that interact with the target of interest. These techniques often utilize biophysical methods such as nuclear magnetic resonance (NMR), X-ray crystallography, and surface plasmon resonance (SPR). These methods are sensitive and can provide detailed insights into the interactions between fragments and their targets. For instance, SPR is highlighted as a powerful tool for studying biomolecular interactions in a label-free format, allowing for the screening of large libraries of small molecules. Recent advancements have enabled the use of chemical microarrays combined with SPR imaging to generate affinity data for numerous protein targets simultaneously, significantly enhancing throughput capabilities in fragment screening [20].

The optimization of fragment hits is crucial for developing high-affinity lead compounds. Once fragments are identified, they can be optimized through various strategies, including fragment growing, merging, and linking. Fragment growing involves adding additional chemical moieties to a fragment to enhance binding affinity, while merging combines two or more fragments to create a larger compound that maintains favorable interactions with the target [5]. Linking strategies also play a role, where fragments are connected to create a more potent inhibitor [1].

Computational approaches are increasingly integral to FBDD, providing support throughout the drug discovery process. These methods allow for the construction of fragment libraries that can be screened virtually against target proteins, thereby expanding the chemical space explored beyond what is feasible with traditional experimental methods. Computational tools facilitate the filtering of large chemical databases to identify suitable fragments based on their physicochemical properties [11].

Moreover, in silico techniques such as molecular docking, pharmacophore modeling, and quantitative structure-activity relationship (QSAR) analysis are employed to predict fragment-target interactions and guide the design of experiments [21]. The integration of computational and experimental methods is emphasized as a powerful strategy, enabling the discovery of high-quality chemical matter through iterative cycles of design, screening, and optimization [22].

In summary, fragment-based drug discovery is a multi-faceted approach that leverages both experimental fragment screening techniques and computational methodologies. This synergy not only enhances the identification of promising drug candidates but also streamlines the optimization process, ultimately contributing to the development of effective therapeutics.

4 Fragment Optimization Strategies

4.1 Fragment Growing

Fragment-based drug discovery (FBDD) is a strategic methodology employed in the identification and optimization of potent lead compounds for drug development. The core principle of FBDD involves starting with small-molecule fragments that typically bind weakly to the target protein. The process encompasses several key steps, particularly focusing on fragment optimization strategies, including fragment growing.

Fragment growing is a critical aspect of FBDD, where the initial weakly binding fragments are systematically optimized to enhance their binding affinity and specificity towards the target. This is achieved through various techniques, such as growing the fragment by adding additional chemical moieties that increase the interaction with the target protein. The aim is to transform these low-affinity fragments into high-affinity ligands that can effectively modulate the target's biological function.

The methodologies employed in fragment growing include biophysical techniques and computational methods. Biophysical methods, such as nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, play a vital role in fragment screening and understanding the binding modes of fragment hits. These techniques provide detailed insights into how fragments interact with their targets, which is crucial for guiding the design of optimized compounds [5][8].

Additionally, fragment growing can be supported by computational approaches, which facilitate the exploration of a vast chemical space. For instance, the use of artificial intelligence (AI) has recently been integrated into fragment growing strategies, enhancing the accuracy and efficiency of molecular design. Techniques such as variational autoencoders (VAE) and reinforcement learning enable precise molecular structure exploration and optimization, allowing for the generation of novel compounds with improved binding affinities [3].

Moreover, fragment linking is another strategy that can complement fragment growing. This involves merging or linking two or more fragments to create a more complex molecule with improved binding characteristics. Structure-based approaches, guided by NMR experiments and molecular dynamics simulations, are utilized to optimize the linking of fragments, thereby enhancing their overall efficacy [5].

In summary, fragment-based drug discovery employs a systematic approach that begins with low-affinity fragments, which are then optimized through fragment growing and linking strategies. The integration of biophysical techniques and computational methods, including AI-driven approaches, has significantly advanced the efficiency of this process, enabling the discovery of high-affinity ligands for various biological targets. This multifaceted strategy is pivotal in the drug discovery landscape, providing a robust framework for developing new therapeutics.

4.2 Fragment Merging

Fragment-based drug discovery (FBDD) is a method that identifies small molecule hits by exploring the chemical space through low molecular weight fragments that typically bind to their target with weak affinity. This approach relies on the rational elaboration of these fragments into high-affinity ligands through various optimization strategies, including fragment merging.

Fragment merging is one of the key strategies in FBDD, where two or more binding fragments are combined to create a new compound that can occupy a larger portion of the target binding site, thereby enhancing binding affinity. This technique has gained traction due to its ability to leverage existing fragment hits to generate more potent compounds. Merging can be performed in a structure-based manner, utilizing techniques such as X-ray crystallography and NMR spectroscopy to inform the design and predict the binding interactions of the new compound.

In a review by Bedwell et al. (2022), it is highlighted that despite the theoretical potential of fragment linking strategies, successful examples remain relatively sparse, overshadowed by the more common practice of fragment growing. The authors emphasize the importance of structure-based approaches, including X-ray crystallography and in silico optimization methods, to facilitate effective fragment merging [5].

Moreover, Yoo et al. (2025) discuss how recent advancements in artificial intelligence (AI) have significantly improved the accuracy and efficiency of molecular design in FBDD. Techniques such as variational autoencoders (VAE), reinforcement learning, and SE(3)-equivariant models have been employed to optimize the merging process, enabling precise exploration of molecular structures and improving the identification of effective lead compounds [3].

Furthermore, the integration of computational methods with experimental approaches enhances the efficiency of fragment merging. Kumar et al. (2012) point out that the combination of computational fragment screening with experimental techniques not only aids in identifying high-quality interactions but also facilitates the transformation of fragments into lead compounds [23].

In summary, fragment merging within FBDD is a sophisticated strategy that combines multiple techniques to optimize the design of new compounds. By merging fragments that exhibit weak binding affinities, researchers can create more potent ligands that have the potential to become effective drugs. The incorporation of advanced computational methods and structural biology techniques further supports the successful application of this strategy in drug discovery.

4.3 Structure-Activity Relationship (SAR) Studies

Fragment-based drug discovery (FBDD) is a strategic approach utilized in the identification and optimization of drug candidates. This methodology focuses on the initial identification of low molecular weight compounds, known as fragments, which exhibit weak binding affinities to specific biological targets. The process of FBDD can be broadly divided into several key components, including fragment identification, optimization, and the application of structure-activity relationship (SAR) studies.

The initial phase of FBDD involves screening a library of fragments against a target protein to identify those that bind effectively, albeit with low affinity. This is typically achieved through biophysical techniques such as nuclear magnetic resonance (NMR), X-ray crystallography, or surface plasmon resonance, which allow for the detection of weak interactions between fragments and the target protein [23]. Once potential fragments are identified, the optimization process begins.

Fragment optimization strategies can be categorized into three primary approaches: fragment growing, merging, and linking. Fragment growing involves the addition of chemical moieties to the existing fragment to enhance binding affinity and specificity. Merging entails combining two or more fragments that bind to adjacent sites on the target, thereby increasing the overall binding affinity. Linking, on the other hand, connects two fragments via a linker to form a more potent ligand [5].

A critical aspect of fragment optimization is the integration of structure-activity relationship (SAR) studies. SAR studies involve analyzing the relationship between the chemical structure of the optimized fragments and their biological activity. This process helps in understanding how modifications to the fragment structure can influence its binding affinity and selectivity towards the target. By employing quantitative structure-activity relationship (QSAR) modeling, researchers can predict the activity of new compounds based on the established SAR data [24].

The combination of SAR studies with computational methodologies enhances the efficiency of fragment optimization. Advanced computational techniques, such as molecular docking and virtual screening, allow for the exploration of a vast chemical space and facilitate the identification of promising candidates for further development [25]. Furthermore, recent advancements in artificial intelligence (AI) and machine learning are being integrated into FBDD, improving the precision and speed of molecular design and optimization [3].

Overall, FBDD represents a powerful and systematic approach to drug discovery, leveraging the identification of low-affinity fragments and their subsequent optimization through well-defined strategies and SAR studies. This methodology not only accelerates the lead optimization process but also contributes to the development of compounds with improved pharmacological profiles, thereby addressing challenges in drug development.

5 Applications and Case Studies

5.1 Successful Drug Candidates Developed via FBDD

Fragment-based drug discovery (FBDD) is a strategic approach that utilizes small molecular fragments as starting points for drug development. The methodology has gained significant traction in both academic and industrial settings due to its ability to identify high-affinity ligands from low-affinity starting points. This process typically involves several key stages: fragment screening, hit identification, fragment optimization, and lead development.

Initially, a library of low molecular weight fragments, typically ranging from 100 to 300 Da, is screened against a target protein. This screening is often conducted using biophysical techniques such as X-ray crystallography, NMR spectroscopy, and surface plasmon resonance. These methods allow for the identification of weakly binding fragments that can interact with the target, despite their low affinity [6][26]. The structural information obtained from these techniques is critical as it helps in understanding the binding modes of the fragments, which can inform subsequent optimization efforts [11].

Once potential fragment hits are identified, they undergo a hit-to-lead process where they are elaborated into more potent compounds. This can involve various strategies such as fragment growing, merging, or linking [5]. The aim is to enhance the binding affinity and selectivity of the fragments towards the target. The optimization process is often guided by iterative cycles of synthesis and testing, leveraging both experimental data and computational modeling [13].

FBDD has been particularly successful in targeting challenging and previously "undruggable" proteins. Notably, several FDA-approved drugs have emerged from this approach. For instance, capivasertib, an inhibitor targeting the AKT pathway in oncology, is a fragment-derived drug that has contributed to the growing portfolio of FBDD-derived therapeutics, which now includes seven approved oncology drugs [1]. The success of FBDD is further illustrated by its application in various therapeutic areas, including cancer and central nervous system disorders, where it has been instrumental in developing compounds that effectively modulate target proteins [27][28].

In conclusion, FBDD represents a powerful and innovative strategy in drug discovery that effectively bridges the gap between initial fragment identification and the development of high-affinity drug candidates. The method's ability to explore a vast chemical space and its successful application to diverse targets underscore its significance in modern medicinal chemistry [8][29].

5.2 Challenges and Limitations of FBDD

Fragment-based drug discovery (FBDD) is a strategic approach in drug development that utilizes small chemical fragments as starting points for identifying potent drug candidates. This methodology has gained traction in both academia and the pharmaceutical industry, particularly for its ability to address complex targets and enhance the hit-to-lead process.

FBDD operates by screening small libraries of low molecular weight compounds, typically ranging from 300 to 500 Da, which are designed to bind to biological targets. The initial hits from this screening often exhibit weak binding affinities. Therefore, the evolution of these fragments into more potent compounds involves several key strategies, including fragment growing, merging, and linking. These strategies enable the enhancement of binding affinity and specificity through structural optimization of the fragments [4][30].

The applications of FBDD are diverse, extending from oncology to infectious diseases. Notably, FBDD has led to the development of several FDA-approved drugs, demonstrating its effectiveness in yielding clinically relevant candidates. For instance, capivasertib is a fragment-derived drug that has contributed to the increasing number of fragment-based oncology therapeutics [1]. Additionally, FBDD has shown promise in targeting previously "undruggable" proteins, thereby expanding the scope of drug discovery [1].

Despite its advantages, FBDD is not without challenges. One significant limitation is the inherent difficulty in detecting weak binding interactions between fragments and their targets. This necessitates the use of sensitive biophysical techniques such as nuclear magnetic resonance (NMR), X-ray crystallography, and surface plasmon resonance, which can be resource-intensive [17]. Furthermore, the need for effective methods to evolve low-affinity fragment hits into high-affinity leads presents an ongoing challenge. The lack of structural information for certain targets can also hinder the optimization process, as it limits the ability to guide fragment modifications effectively [19].

Moreover, the library design poses its own set of challenges, as the selection of fragments must ensure adequate coverage of the chemical space while maintaining the potential for biological activity [16]. The integration of FBDD with high-throughput screening (HTS) is also being explored to enhance the discovery process for druggable targets, yet this requires careful planning and execution [31].

In summary, FBDD is a powerful methodology in drug discovery that effectively leverages small molecular fragments to identify and optimize drug candidates. While it presents unique challenges, ongoing advancements in screening techniques and structural biology are likely to enhance its application and success in developing new therapeutics across various disease areas.

6 Future Perspectives in FBDD

6.1 Emerging Technologies

Fragment-based drug discovery (FBDD) is a method that utilizes small molecular fragments, typically with a molecular weight of less than 300 Da, as starting points for drug discovery. This approach allows for the identification of low molecular weight compounds that can bind to biological targets, such as proteins, and serves as a foundation for the development of more potent drug candidates. The methodology relies on several key features and technologies that have evolved significantly over the years.

The FBDD process begins with the screening of a fragment library against a target of clinical relevance. This library is composed of small fragments that generally exhibit weak binding affinities. However, these fragments are capable of forming efficient and high-quality interactions with the target protein architecture, overcoming a significant entropy barrier to achieve binding [6]. Biophysical techniques such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and surface plasmon resonance are commonly employed to assess fragment binding and to provide detailed structural information about the protein-fragment complex [6][11].

The future perspectives of FBDD are promising, particularly with the integration of advanced technologies. Emerging computational tools and methodologies, such as machine learning and deep learning models, are being increasingly incorporated into the FBDD workflow. These technologies can facilitate the virtual screening of vast chemical spaces, optimizing the identification of fragments that are likely to lead to successful drug candidates [32]. Furthermore, advancements in fragment library design, including the creation of diverse and three-dimensional fragment collections through diversity-oriented synthesis, are enhancing the effectiveness of FBDD [33].

As FBDD continues to evolve, its applicability to a wider range of targets, including previously "undruggable" proteins and complex biological systems, is becoming evident. The integration of high-throughput methodologies, such as massively parallel screening techniques using X-ray crystallography, is also expected to streamline the drug discovery process, allowing for more efficient identification and optimization of lead compounds [34].

Moreover, the exploration of novel fragment linking strategies, which involve the merging or linking of fragments to form higher-affinity ligands, presents a significant area for future research. This approach aims to capitalize on the structural insights gained from fragment screening to develop more potent and selective drug candidates [5].

In conclusion, fragment-based drug discovery represents a dynamic and evolving field that leverages small molecular fragments as starting points for drug development. With ongoing advancements in technology and methodology, FBDD is poised to play a pivotal role in addressing unmet therapeutic needs across various disease areas, ultimately leading to the discovery of innovative and effective treatments.

6.2 Integration with Other Drug Discovery Approaches

Fragment-based drug discovery (FBDD) is a sophisticated strategy employed in drug discovery that focuses on identifying small molecular fragments that can bind to biological targets. This method capitalizes on the ability of these low-molecular-weight compounds, typically ranging from 100 to 300 Da, to provide a robust foundation for the development of drug candidates. The fundamental process involves several critical steps: the screening of fragment libraries against target proteins, the identification of fragment hits, and the subsequent optimization of these fragments into lead compounds.

The screening phase utilizes various biophysical techniques, such as X-ray crystallography, nuclear magnetic resonance (NMR), and surface plasmon resonance, to detect weak interactions between the fragments and the target proteins. These methods are particularly advantageous because they allow for the structural characterization of fragment binding, providing insights into binding modes and facilitating further optimization of the fragments [6][11]. The weak affinity of fragments is not a limitation; rather, it enables the identification of high-quality binding interactions that can be refined into more potent compounds [9].

The integration of computational tools enhances the efficiency of FBDD by enabling rational drug design. These tools assist in the screening process, filtering chemical databases to create focused fragment libraries, and employing structure-activity relationship (SAR) models to predict the behavior of compounds [32]. The synergy between biophysical techniques and computational methods has significantly improved the success rate of fragment-based approaches, allowing researchers to tackle challenging targets that may have previously been deemed "undruggable" [13].

Looking to the future, FBDD is poised to expand its role in drug discovery, particularly as the field moves beyond traditional druggable targets. The ongoing advancements in fragment libraries, screening methodologies, and computational techniques are expected to further streamline the drug discovery process [1]. As the methodology continues to evolve, it will likely incorporate innovative strategies such as fragment linking and merging, which can facilitate the development of high-affinity ligands from initially weak-binding fragments [5].

FBDD's integration with other drug discovery approaches, such as high-throughput screening (HTS) and structure-based drug design (SBDD), is essential for maximizing its potential. While HTS allows for the rapid screening of large compound libraries, FBDD complements this by providing a more nuanced understanding of the binding interactions at play, thus guiding the design of more effective compounds [35]. Furthermore, the combination of FBDD with SBDD enhances the ability to design targeted therapies by leveraging structural information about the target proteins, thereby facilitating the development of more selective and potent drug candidates [19].

In conclusion, FBDD represents a transformative approach in the field of medicinal chemistry, offering a systematic method for drug discovery that effectively bridges the gap between fragment identification and lead optimization. Its future is bright, with the potential for continued innovation and integration with other methodologies, promising a new era of drug discovery that addresses previously unmet therapeutic needs.

7 Conclusion

Fragment-based drug discovery (FBDD) has emerged as a pivotal methodology in the field of drug discovery, addressing the limitations of traditional approaches and expanding the horizons of therapeutic development. Its core principle of utilizing small molecular fragments as starting points has proven effective in identifying high-affinity ligands, particularly for previously 'undruggable' targets. The systematic processes of fragment screening, optimization, and iterative refinement have facilitated the development of numerous clinically relevant drugs, showcasing the potential of FBDD to revolutionize therapeutic options across various disease areas. Despite the inherent challenges associated with weak binding affinities and the need for sophisticated biophysical techniques, ongoing advancements in computational methods and structural biology are enhancing the efficiency and success of FBDD. The future of FBDD looks promising, with the integration of emerging technologies and collaborative approaches likely to further streamline the drug discovery process. As the field continues to evolve, FBDD will play an increasingly critical role in addressing unmet medical needs, ultimately leading to the discovery of innovative and effective treatments.

References

• [1] Nilesh Raghunath Khedkar;Milind Sindkhedkar;Alex Joseph. Fragment-Based Drug Discovery: Small Fragments, Big Impact - Success Stories of Approved Oncology Therapeutics.. Bioorganic chemistry(IF=4.7). 2025. PMID:39879825. DOI: 10.1016/j.bioorg.2025.108197.
• [2] Qingxin Li. Application of Fragment-Based Drug Discovery to Versatile Targets.. Frontiers in molecular biosciences(IF=4.0). 2020. PMID:32850968. DOI: 10.3389/fmolb.2020.00180.
• [3] Jinhyeok Yoo;Wonkyeong Jang;Woong-Hee Shin. From part to whole: AI-driven progress in fragment-based drug discovery.. Current opinion in structural biology(IF=7.0). 2025. PMID:39970579. DOI: 10.1016/j.sbi.2025.102995.
• [4] Tim Kirkman;Catharina Dos Santos Silva;Manuela Tosin;Marcio Vinicius Bertacine Dias. How to Find a Fragment: Methods for Screening and Validation in Fragment-Based Drug Discovery.. ChemMedChem(IF=3.4). 2024. PMID:39198213. DOI: 10.1002/cmdc.202400342.
• [5] Elizabeth V Bedwell;William J McCarthy;Anthony G Coyne;Chris Abell. Development of potent inhibitors by fragment-linking strategies.. Chemical biology & drug design(IF=3.3). 2022. PMID:35854428. DOI: 10.1111/cbdd.14120.
• [6] Amanda J Price;Steven Howard;Benjamin D Cons. Fragment-based drug discovery and its application to challenging drug targets.. Essays in biochemistry(IF=5.7). 2017. PMID:29118094. DOI: 10.1042/EBC20170029.
• [7] Aanchal Kashyap;Pankaj Kumar Singh;Om Silakari. Counting on Fragment Based Drug Design Approach for Drug Discovery.. Current topics in medicinal chemistry(IF=3.3). 2018. PMID:30499406. DOI: 10.2174/1568026619666181130134250.
• [8] Qingxin Li;Congbao Kang. Perspectives on Fragment-based Drug Discovery: A Strategy Applicable to Diverse Targets.. Current topics in medicinal chemistry(IF=3.3). 2021. PMID:34348623. DOI: 10.2174/1568026621666210804115700.
• [9] Leonardo G Ferreira;Adriano D Andricopulo. From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.. Current topics in medicinal chemistry(IF=3.3). 2017. PMID:28240184. DOI: 10.2174/1568026617666170224113437.
• [10] Gerdien E de Kloe;David Bailey;Rob Leurs;Iwan J P de Esch. Transforming fragments into candidates: small becomes big in medicinal chemistry.. Drug discovery today(IF=7.5). 2009. PMID:19443265. DOI: 10.1016/j.drudis.2009.03.009.
• [11] Rafael Gozalbes;Rodrigo J Carbajo;Antonio Pineda-Lucena. Contributions of computational chemistry and biophysical techniques to fragment-based drug discovery.. Current medicinal chemistry(IF=3.5). 2010. PMID:20345344. DOI: 10.2174/092986710791111224.
• [12] Andrew P Turnbull;Susan M Boyd. Targeting cancer using fragment based drug discovery.. Anti-cancer agents in medicinal chemistry(IF=3.0). 2012. PMID:21707503. DOI: 10.2174/187152012798764660.
• [13] Weijun Xu;Congbao Kang. Fragment-Based Drug Design: From Then until Now, and Toward the Future.. Journal of medicinal chemistry(IF=6.8). 2025. PMID:39992814. DOI: 10.1021/acs.jmedchem.5c00424.
• [14] Daniel Shiu-Hin Chan;Andrew J Whitehouse;Anthony G Coyne;Chris Abell. Mass spectrometry for fragment screening.. Essays in biochemistry(IF=5.7). 2017. PMID:28986384. DOI: 10.1042/EBC20170071.
• [15] Iva Navratilova;Andrew L Hopkins. Fragment screening by surface plasmon resonance.. ACS medicinal chemistry letters(IF=4.0). 2010. PMID:24900174. DOI: 10.1021/ml900002k.
• [16] Krystian Eitner;Uwe Koch. From fragment screening to potent binders: strategies for fragment-to-lead evolution.. Mini reviews in medicinal chemistry(IF=3.3). 2009. PMID:19601891. DOI: 10.2174/138955709788681645.
• [17] Anja Winter;Alicia P Higueruelo;May Marsh;Anna Sigurdardottir;Will R Pitt;Tom L Blundell. Biophysical and computational fragment-based approaches to targeting protein-protein interactions: applications in structure-guided drug discovery.. Quarterly reviews of biophysics(IF=5.3). 2012. PMID:22971516. DOI: 10.1017/S0033583512000108.
• [18] Hugo O Villar;Mark R Hansen. Computational techniques in fragment based drug discovery.. Current topics in medicinal chemistry(IF=3.3). 2007. PMID:17897037. DOI: 10.2174/156802607782194725.
• [19] Gregg Siegal;Eiso Ab;Jan Schultz. Integration of fragment screening and library design.. Drug discovery today(IF=7.5). 2007. PMID:18061882. DOI: 10.1016/j.drudis.2007.08.005.
• [20] T Neumann;H-D Junker;K Schmidt;R Sekul. SPR-based fragment screening: advantages and applications.. Current topics in medicinal chemistry(IF=3.3). 2007. PMID:17979772. DOI: 10.2174/156802607782341073.
• [21] Jeremie Mortier;Christin Rakers;Raphael Frederick;Gerhard Wolber. Computational tools for in silico fragment-based drug design.. Current topics in medicinal chemistry(IF=3.3). 2012. PMID:23116473. DOI: 10.2174/156802612804547371.
• [22] Diane Joseph-McCarthy;Arthur J Campbell;Gunther Kern;Demetri Moustakas. Fragment-based lead discovery and design.. Journal of chemical information and modeling(IF=5.3). 2014. PMID:24490951. DOI: 10.1021/ci400731w.
• [23] A Kumar;A Voet;K Y J Zhang. Fragment based drug design: from experimental to computational approaches.. Current medicinal chemistry(IF=3.5). 2012. PMID:22934764. DOI: 10.2174/092986712803530467.
• [24] Valeria V Kleandrova;Alejandro Speck-Planche. The QSAR Paradigm in Fragment-Based Drug Discovery: From the Virtual Generation of Target Inhibitors to Multi-Scale Modeling.. Mini reviews in medicinal chemistry(IF=3.3). 2020. PMID:32013845. DOI: 10.2174/1389557520666200204123156.
• [25] Axel Rudling;Robert Gustafsson;Ingrid Almlöf;Evert Homan;Martin Scobie;Ulrika Warpman Berglund;Thomas Helleday;Pål Stenmark;Jens Carlsson. Fragment-Based Discovery and Optimization of Enzyme Inhibitors by Docking of Commercial Chemical Space.. Journal of medicinal chemistry(IF=6.8). 2017. PMID:28929756. DOI: 10.1021/acs.jmedchem.7b01006.
• [26] Christopher W Murray;Marcel L Verdonk;David C Rees. Experiences in fragment-based drug discovery.. Trends in pharmacological sciences(IF=19.9). 2012. PMID:22459076. DOI: 10.1016/j.tips.2012.02.006.
• [27] Bill W G L Chan;Nicholas B Lynch;Wendy Tran;Jack M Joyce;G Paul Savage;Wim Meutermans;Andrew P Montgomery;Michael Kassiou. Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece.. Frontiers in chemistry(IF=4.2). 2024. PMID:38698940. DOI: 10.3389/fchem.2024.1379518.
• [28] Janis Müller;Raphael Klein;Olga Tarkhanova;Anastasiia Gryniukova;Petro Borysko;Stefan Merkl;Moritz Ruf;Alexander Neumann;Marcus Gastreich;Yurii S Moroz;Gerhard Klebe;Serghei Glinca. Magnet for the Needle in Haystack: "Crystal Structure First" Fragment Hits Unlock Active Chemical Matter Using Targeted Exploration of Vast Chemical Spaces.. Journal of medicinal chemistry(IF=6.8). 2022. PMID:36069712. DOI: 10.1021/acs.jmedchem.2c00813.
• [29] Masaya Orita;Masaichi Warizaya;Yasushi Amano;Kazuki Ohno;Tatsuya Niimi. Advances in fragment-based drug discovery platforms.. Expert opinion on drug discovery(IF=4.9). 2009. PMID:23480433. DOI: 10.1517/17460440903317580.
• [30] James Osborne;Stanislava Panova;Magdalini Rapti;Tatsuya Urushima;Harren Jhoti. Fragments: where are we now?. Biochemical Society transactions(IF=4.3). 2020. PMID:31985743. DOI: 10.1042/BST20190694.
• [31] Bas Lamoree;Roderick E Hubbard. Current perspectives in fragment-based lead discovery (FBLD).. Essays in biochemistry(IF=5.7). 2017. PMID:29118093. DOI: 10.1042/EBC20170028.
• [32] Lauro Ribeiro de Souza Neto;José Teófilo Moreira-Filho;Bruno Junior Neves;Rocío Lucía Beatriz Riveros Maidana;Ana Carolina Ramos Guimarães;Nicholas Furnham;Carolina Horta Andrade;Floriano Paes Silva. In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery.. Frontiers in chemistry(IF=4.2). 2020. PMID:32133344. DOI: 10.3389/fchem.2020.00093.
• [33] Sarah L Kidd;Thomas J Osberger;Natalia Mateu;Hannah F Sore;David R Spring. Recent Applications of Diversity-Oriented Synthesis Toward Novel, 3-Dimensional Fragment Collections.. Frontiers in chemistry(IF=4.2). 2018. PMID:30386766. DOI: 10.3389/fchem.2018.00460.
• [34] Namdev S Togre;Ana M Vargas;Gunapati Bhargavi;Mohan Krishna Mallakuntla;Sangeeta Tiwari. Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges.. International journal of molecular sciences(IF=4.9). 2022. PMID:36142582. DOI: 10.3390/ijms231810669.
• [35] Masaya Orita;Kazuki Ohno;Tatsuya Niimi. Two 'Golden Ratio' indices in fragment-based drug discovery.. Drug discovery today(IF=7.5). 2009. PMID:19028598. DOI: 10.1016/j.drudis.2008.10.006.

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