Linkers in fragment-based drug design: an overview of the literature

INTRODUCTION

In fragment-based drug design, fragment linking is a popular strategy where two fragments binding to different sub-pockets of a target are linked together. This attractive method remains challenging especially due to the design of ideal linkers.

AREAS COVERED

The authors review the types of linkers and chemical reactions commonly used to the synthesis of linkers, including those utilized in protein-templated fragment self-assembly, where fragments are directly linked in the presence of the protein. Finally, they detail computational workflows and software including generative models that have been developed for fragment linking.

EXPERT OPINION

The authors believe that fragment linking offers key advantages for compound design, particularly for the design of bivalent inhibitors linking two distinct pockets of the same or different subunits. On the other hand, more studies are needed to increase the potential of protein-templated approaches in FBDD. Important computational tools such as structure-based de novo software are emerging to select suitable linkers. Fragment linking will undoubtedly benefit from developments in computational approaches and machine learning models.

Development of potent inhibitors by fragment-linking strategies

Fragment-based drug discovery (FBDD) is a method of identifying small molecule hits that can be elaborated rationally through fragment growing, merging, and linking, to afford high affinity ligands for biological targets. Despite the promised theoretical potential of fragment linking, examples are still surprisingly sparse and remain overshadowed by the successes of fragment growing. The aim of this review is to outline a number of key examples of fragment linking strategies and discuss their strengths and limitations. Structure-based approaches including X-ray crystallography and in silico methods fragment optimisation are discussed, as well as fragment linking guided by NMR experiments. Target-guided approaches, exploiting the biological target to assemble its own inhibitors through dynamic combinatorial chemistry (DCC) and kinetic target-guided synthesis (KTGS), are identified as alternative efficient methods for fragment linking.

Fragment molecular orbital calculations for biomolecules

Exploring biomolecule behavior, such as proteins and nucleic acids, using quantum mechanical theory can identify many life science phenomena from first principles. Fragment molecular orbital (FMO) calculations of whole single particles of biomolecules can determine the electronic state of the interior and surface of molecules and explore molecular recognition mechanisms based on intermolecular and intramolecular interactions. In this review, we summarized the current state of FMO calculations in drug discovery, virology, and structural biology, as well as recent developments from data science.

Luteolin: a blocker of SARS-CoV-2 cell entry based on relaxed complex scheme, molecular dynamics simulation, and metadynamics

Natural products have served human life as medications for centuries. During the outbreak of COVID-19, a number of naturally derived compounds and extracts have been tested or used as potential remedies against COVID-19. Tetradenia riparia extract is one of the plant extracts that have been deployed and claimed to manage and control COVID-19 by some communities in Tanzania and other African countries. The active compounds isolated from T. riparia are known to possess various biological properties including antimalarial and antiviral. However, the underlying mechanism of the active compounds against SARS-CoV-2 remains unknown. Results in the present work have been interpreted from the view point of computational methods including molecular dynamics, free energy methods, and metadynamics to establish the related mechanism of action. Among the constituents of T. riparia studied, luteolin inhibited viral cell entry and was thermodynamically stable. The title compound exhibit residence time and unbinding kinetics of 68.86 ms and 0.014 /ms, respectively. The findings suggest that luteolin could be potent blocker of SARS-CoV-2 cell entry. The study shades lights towards identification of bioactive constituents from T. riparia against COVID-19, and thus bioassay can be carried out to further validate such observations.

Guiding Medicinal Chemistry with Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between a protein and a small molecule plays a key role in the rationalization of potency and selectivity and in design of new ideas. However, even when a target of interest is structurally enabled, visual inspection and force field-based molecular mechanics calculations cannot always explain the full complexity of the molecular interactions that are critical in drug design. Quantum mechanical methods have the potential to address this shortcoming, but traditionally, computational expense has made the application of these calculations impractical. The fragment molecular orbital (FMO) method offers a solution that combines accuracy, speed, and the ability to characterize important interactions (i.e. its strength in kcal/mol and chemical nature: hydrophobic, electrostatic, etc) that would otherwise be hard to detect. In this chapter, we describe the FMO method and illustrate its application in the discovery of the benzothiazole (BZT) series as novel tyrosine kinase ITK inhibitors for treatment of allergic asthma.

Analyzing GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

G-protein-coupled receptors (GPCRs) have enormous physiological and biomedical importance, and therefore it is not surprising that they are the targets of many prescribed drugs. Further progress in GPCR drug discovery is highly dependent on the availability of protein structural information. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanics (QM) approaches are often too computationally expensive to be of practical use in time-sensitive situations, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed, and the ability to reveal key interactions that would otherwise be hard to detect. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule toward ligand binding, including an analysis of their chemical nature. Such information is essential for an efficient structure-based drug design (SBDD) process. In this chapter, we describe how to use FMO in the characterization of GPCR-ligand interactions.

General Theory of Fragment Linking in Molecular Design: Why Fragment Linking Rarely Succeeds and How to Improve Outcomes

Linking two fragments binding in nearby subpockets together has become an important technique in fragment-based drug discovery to optimize the binding potency of fragment hits. Despite the expected favorable translational and orientational entropic contribution to the binding free energy of the linked molecule, brute force enumeration of chemical linker for linking fragments is rarely successful, and the vast majority of linked molecules do not exhibit the expected gains of binding potency. In this paper, we examine the physical factors that contribute to the change of binding free energy from fragment linking and develop a method to rigorously calculate these different physical contributions. We find from these analyses that multiple confounding factors make successful fragment linking strategies rare, including (1) possible change of the binding mode of the fragments in the linked state compared to separate binding of the fragments, (2) unfavorable intramolecular strain energy of the bioactive conformation of the linked molecule, (3) unfavorable interaction between the linker and the protein, (4) favorable interaction energies between two fragments in solution when not chemically linked that offset the expected entropy loss for the formation of fragment pair, (5) complex compensating configurational entropic effects beyond the simplistic rotational and translational analysis. We here have applied a statistically mechanically rigorous approach to compute the fragment linking coefficients of 10 pharmaceutically interesting systems and quantify the contribution of each physical component to the binding free energy of the linked molecule. Based on these studies, we have found that the change in the relative configurational entropy of the two fragments in the protein binding pocket (a term neglected to our knowledge in all previous analyses) substantially offsets the favorable expected rotational and translational entropic contributions to the binding free energy of the linked molecule. This configurational restriction of the fragments in the binding pocket of the proteins is found to be, in our analysis, the dominant reason why most fragment linking strategies do not exhibit the expected gains of binding potency. These findings have further provided rich physical insights, which we expect should facilitate more successful fragment linking strategies to be formulated in the future.

Characterizing Interhelical Interactions of G-Protein Coupled Receptors with the Fragment Molecular Orbital Method

G-protein coupled receptors (GPCRs) are the largest superfamily of membrane proteins, regulating almost every aspect of cellular activity and serving as key targets for drug discovery. We have identified an accurate and reliable computational method to characterize the strength and chemical nature of the interhelical interactions between the residues of transmembrane (TM) domains during different receptor activation states, something that cannot be characterized solely by visual inspection of structural information. Using the fragment molecular orbital (FMO) quantum mechanics method to analyze 35 crystal structures representing different branches of the class A GPCR family, we have identified 69 topologically equivalent TM residues that form a consensus network of 51 inter-TM interactions, providing novel results that are consistent with and help to rationalize experimental data. This discovery establishes a comprehensive picture of how defined molecular forces govern specific interhelical interactions which, in turn, support the structural stability, ligand binding, and activation of GPCRs.

A computational study on the role of water and conformational fluctuations in Hsp90 in response to inhibitors

Molecular chaperone Heat Shock Protein 90 (Hsp90) represents an interesting chemotherapeutic target for cancer treatments as it plays a role in cancer proliferation. Thus, continued effort to identify novel inhibitors of this target is an important task. Drug design using computational approach has gained significant attention in recent years. This work aims to propose docking protocols to re-purpose FDA-approved drugs targeting Hsp90. Sensitivity of results to different docking protocols such apo, holo and receptor ensembles (relaxed complex) structures, the role of water and conformational changes of Hsp90, are described. We show that the protein conformation and water have effects on drug binding. Holo relaxed complex receptors ensembles improves the binding energy of ligands to the protein. We also compare and contrast structural stability of three drugs namely: ezetimibe, pitavastatin and vilazodon in the Hsp90 protein. The results obtained serves as a possible basis towards developing Hsp90 inhibitors.

Characterising GPCR-ligand interactions using a fragment molecular orbital-based approach

There has been fantastic progress in solving GPCR crystal structures. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanical approaches (QM) are often too computationally expensive, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed and the ability to reveal key interactions that would otherwise be hard to detect. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule towards ligand binding, including an analysis of their chemical nature.

Chemistry-driven Hit-to-lead Optimization Guided by Structure-based Approaches

For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated. However, it is also crucial to consider the feasibility of organically synthesizing these virtually designed compounds. Furthermore, the generated molecules should have reasonable physicochemical properties and be medicinally relevant. This review focuses on chemistry-driven and structure-based computational methods that can be used to tackle the difficult problem of H2L optimization, with emphasis being placed on the strategy developed in our laboratory.

Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity. It is essential for an efficient structure-based drug design (SBDD) process. FMO enables ab initio approaches to be applied to systems that conventional quantum-mechanical (QM) methods would find challenging. The key advantage of the Fragment Molecular Orbital Method (FMO) is that it can reveal atomistic details about the individual contributions and chemical nature of each residue and water molecule toward ligand binding which would otherwise be difficult to detect without using QM methods. In this chapter, we demonstrate the typical use of FMO to analyze 19 crystal structures of β1 and β2 adrenergic receptors with their corresponding agonists and antagonists.

Impact of a Central Scaffold on the Binding Affinity of Fragment Pairs Isolated from DNA-Encoded Self-Assembling Chemical Libraries

The screening of encoded self-assembling chemical libraries allows the identification of fragment pairs that bind to adjacent pockets on target proteins of interest. For practical applications, it is necessary to link these ligand pairs into discrete organic molecules, devoid of any nucleic acid component. Here we describe the discovery of a synergistic binding pair for acid alpha-1 glycoprotein and a chemical strategy for the identification of optimal linkers, connecting the two fragments. The procedure yielded a set of small organic ligands, the best of which exhibited a dissociation constant of 9.9 nm, as measured in solution by fluorescence polarization.

Using the fragment molecular orbital method to investigate agonist-orexin-2 receptor interactions

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in 'real-time' and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allowsab initioapproaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure-function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available.

Fragment-Based Drug Design Facilitated by Protein-Templated Click Chemistry: Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin

There is an urgent need for the development of efficient methodologies that accelerate drug discovery. We demonstrate that the strategic combination of fragment linking/optimization and protein-templated click chemistry is an efficient and powerful method that accelerates the hit-identification process for the aspartic protease endothiapepsin. The best binder, which inhibits endothiapepsin with an IC50 value of 43 μm, represents the first example of triazole-based inhibitors of endothiapepsin. Our strategy could find application on a whole range of drug targets.

Fragment Molecular Orbital Method Applied to Lead Optimization of Novel Interleukin-2 Inducible T-Cell Kinase (ITK) Inhibitors

Inhibition of inducible T-cell kinase (ITK), a nonreceptor tyrosine kinase, may represent a novel treatment for allergic asthma. In our previous reports, we described the discovery of sulfonylpyridine (SAP), benzothiazole (BZT), indazole (IND), and tetrahydroindazole (THI) series as novel ITK inhibitors and how computational tools such as dihedral scans and docking were used to support this process. X-ray crystallography and modeling were applied to provide essential insight into ITK-ligand interactions. However, "visual inspection" traditionally used for the rationalization of protein-ligand affinity cannot always explain the full complexity of the molecular interactions. The fragment molecular orbital (FMO) quantum-mechanical (QM) method provides a complete list of the interactions formed between the ligand and protein that are often omitted from traditional structure-based descriptions. FMO methodology was successfully used as part of a rational structure-based drug design effort to improve the ITK potency of high-throughput screening hits, ultimately delivering ligands with potency in the subnanomolar range.

Docking and Linking of Fragments To Discover Jumonji Histone Demethylase Inhibitors

Development of tool molecules that inhibit Jumonji demethylases allows for the investigation of cancer-associated transcription. While scaffolds such as 2,4-pyridinedicarboxylic acid (2,4-PDCA) are potent inhibitors, they exhibit limited selectivity. To discover new inhibitors for the KDM4 demethylases, enzymes overexpressed in several cancers, we docked a library of 600,000 fragments into the high-resolution structure of KDM4A. Among the most interesting chemotypes were the 5-aminosalicylates, which docked in two distinct but overlapping orientations. Docking poses informed the design of covalently linked fragment compounds, which were further derivatized. This combined approach improved affinity by ∼ 3 log-orders to yield compound 35 (Ki = 43 nM). Several hybrid inhibitors were selective for KDM4C over the related enzymes FIH, KDM2A, and KDM6B while lacking selectivity against the KDM3 and KDM5 subfamilies. Cocrystal structures corroborated the docking predictions. This study extends the use of structure-based docking from fragment discovery to fragment linking optimization, yielding novel KDM4 inhibitors.

The Fragment Molecular Orbital Method Reveals New Insight into the Chemical Nature of GPCR–Ligand Interactions

Our interpretation of ligand-protein interactions is often informed by high-resolution structures, which represent the cornerstone of structure-based drug design. However, visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum Mechanics approaches are often too computationally expensive, but one method, Fragment Molecular Orbital (FMO), offers an excellent compromise and has the potential to reveal key interactions that would otherwise be hard to detect. To illustrate this, we have applied the FMO method to 18 Class A GPCR-ligand crystal structures, representing different branches of the GPCR genome. Our work reveals key interactions that are often omitted from structure-based descriptions, including hydrophobic interactions, nonclassical hydrogen bonds, and the involvement of backbone atoms. This approach provides a more comprehensive picture of receptor-ligand interactions than is currently used and should prove useful for evaluation of the chemical nature of ligand binding and to support structure-based drug design.

Evaluation of a semi-automated workflow for fragment growing

Intelligent Automatic Design (IADE) is an expert system developed at Novartis to identify nonclassical bioisosteres. In addition to bioisostere searching, one could also use IADE to grow a fragment bound to a protein. Here we report an evaluation of IADE as a tool for fragment growing. Three examples from the literature served as test cases. In all three cases, IADE generated close analogues of the published compounds and reproduced their crystallographic binding modes. This exercise validated the use of the IADE system for fragment growing. We have also gained experience in optimizing the performance of IADE for this type of application.

Fragment-based hit discovery and structure-based optimization of aminotriazoloquinazolines as novel Hsp90 inhibitors

In the last decade the heat shock protein 90 (Hsp90) has emerged as a major therapeutic target and many efforts have been dedicated to the discovery of Hsp90 inhibitors as new potent anticancer agents. Here we report the identification of a novel class of Hsp90 inhibitors by means of a biophysical FAXS-NMR based screening of a library of fragments. The use of X-ray structure information combined with modeling studies enabled the fragment evolution of the initial triazoloquinazoline hit to a class of compounds with nanomolar potency and drug-like properties suited for further lead optimization.

Hsp90 inhibitors, part 2: combining ligand-based and structure-based approaches for virtual screening application

Hsp90 continues to be an important target for pharmaceutical discovery. In this project, virtual screening (VS) for novel Hsp90 inhibitors was performed using a combination of Autodock and Surflex-Sim (LB) scoring functions with the predictive ability of 3-D QSAR models, previously generated with the 3-D QSAutogrid/R procedure. Extensive validation of both structure-based (SB) and ligand-based (LB), through realignments and cross-alignments, allowed the definition of LB and SB alignment rules. The mixed LB/SB protocol was applied to virtually screen potential Hsp90 inhibitors from the NCI Diversity Set composed of 1785 compounds. A selected ensemble of 80 compounds were biologically tested. Among these molecules, preliminary data yielded four derivatives exhibiting IC50 values ranging between 18 and 63 μM as hits for a subsequent medicinal chemistry optimization procedure.

Fragment-based Drug Discovery: the Shape of Things to Come

Fragment-Based Drug Discovery (FBDD) is here to stay. Validated as a technology with the delivery of Zelboraf (Vemurafenib) for the treatment of mutant B-RafV600E melanoma, it has become embedded within the pharmaceutical and biotechnology industries. FBDD has delivered clinical development candidates for a broad range of targets including some of the most challenging cases such as β-secretase (BACE1) and protein–protein interactions. But the best is surely still to come.

S4MPLE--sampler for multiple protein-ligand entities: simultaneous docking of several entities

S4MPLE is a conformational sampling tool, based on a hybrid genetic algorithm, simulating one (conformer enumeration) or more molecules (docking). Energy calculations are based on the AMBER force field [Cornell et al. J. Am. Chem. Soc. 1995, 117, 5179.] for biological macromolecules and its generalized version GAFF [Wang et al. J. Comput. Chem. 2004 , 25, 1157.] for ligands. This paper describes more advanced, specific applications of S4MPLE to problems more complex than classical redocking of drug-like compounds [Hoffer et al. J. Mol. Graphics Modell. 2012, submitted for publication.]. Here, simultaneous docking of multiple entities is addressed in two different important contexts. First, simultaneous docking of two fragment-like ligands was attempted, as such ternary complexes are the basis of fragment-based drug design by linkage of the independent binders. As a preliminary, the capacity of S4MPLE to dock fragment-like compounds has been assessed, since this class of small probes used in fragment-based drug design covers a different chemical space than drug-like molecules. Herein reported success rates from fragments redocking are as good as classical benchmarking results on drug-like compounds (Astex Diverse Set [Hartshorn et al. J. Med. Chem. 2007, 50, 726.]). Then, S4MPLE is successfully challenged to predict locations of fragments involved in ternary complexes by means of multientity docking. Second, the key problem of predicting water-mediated interaction is addressed by considering explicit water molecules as additional entities to be docked in the presence of the "main" ligand. Blind prediction of solvent molecule positions, reproducing relevant ligand-water-site mediated interactions, is achieved in 76% cases over saved poses. S4MPLE was also successful to predict crystallographic water displacement by a therefore tailored functional group in the optimized ligand. However, water localization is an extremely delicate issue in terms of weighing of electrostatic and desolvation terms and also introduces a significant increase of required sampling efforts. Yet, the herein reported results - not making use of massively parallel deployment of the software - are very encouraging.

Experiences in fragment-based drug discovery

Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches.

Design and synthesis of novel lactate dehydrogenase A inhibitors by fragment-based lead generation

Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate, utilizing NADH as a cofactor. It has been identified as a potential therapeutic target in the area of cancer metabolism. In this manuscript we report our progress using fragment-based lead generation (FBLG), assisted by X-ray crystallography to develop small molecule LDHA inhibitors. Fragment hits were identified through NMR and SPR screening and optimized into lead compounds with nanomolar binding affinities via fragment linking. Also reported is their modification into cellular active compounds suitable for target validation work.

A small nonrule of 3 compatible fragment library provides high hit rate of endothiapepsin crystal structures with various fragment chemotypes

Druglike molecules are defined by Lipinski's rule of 5, to characterize fragment thresholds, they have been reduced from 5 to 3 (Astex's rule of 3). They are applied to assemble fragment libraries, and providers use them to select fragments for commercial offer. We question whether these rules are too stringent to compose fragment libraries with candidates exhibiting sufficient room for chemical subsequent growing and merging modifications as appropriate functional groups for chemical transformations are required. Usually these groups exhibit properties as hydrogen bond donors/acceptors and provide entry points for optimization chemistry. We therefore designed a fragment library (364 entries) without strictly applying the rule of 3. For initial screening for endothiapepsin binding, we performed a biochemical cleavage assay of a fluorogenic substrate at 1 mM. "Hits" were defined to inhibit the enzyme by at least 40%. Fifty-five hits were suggested and subsequently soaked into endothiapepsin crystals. Eleven crystal structures could be determined covering fragments with diverse binding modes: (i) direct binding to the catalytic dyad aspartates, (ii) water-mediated binding to the aspartates, (iii) no direct interaction with the dyad. They occupy different specificity pockets. Only 4 of the 11 fragments are consistent with the rule of 3. Restriction to this rule would have limited the fragment hits to a strongly reduced variety of chemotypes.

The benefits of constructing leads from fragment hits

‘Fragments’ refer to particularly small molecular starting points in medicinal chemistry. The small size of fragments requires adapted techniques for their screening and subsequent elaboration. The detection of the weak binding affinity of fragments for their target, and associated screening issues, have been debated at length. Since it is now clear that fragments can be developed into clinical candidates, the discussion is shifting to the design of good-quality lead compounds from fragment hits. The increasing ability to control and tailor this construction process highlights the potential benefits of fragment-based drug discovery.

Compound Design by Fragment-Linking

The linking together of two fragment compounds that bind to distinct protein sub-sites can lead to a superadditivity of binding affinities, in which the binding free energy of the linked fragments exceeds the simple sum of the binding energies of individual fragments (linking coefficient E<1). However, a review of the literature shows that such events are relatively rare and, in the majority of the cases, linking coefficients are far from optimal being much greater than 1. It is critical to design a linker that does not disturb the original binding poses of each fragment in order to achieve successful linking. However, such an ideal linker is often difficult to design and even more difficult to actually synthesize. We suggest that the chance of achieving successful fragment linking can be significantly improved by choosing a fragment pair that consists of one fragment that binds by strong H-bonds (or non-classical equivalents) and a second fragment that is more tolerant of changes in binding mode (hydrophobic or vdW binders). We also propose that the fragment molecular orbital (FMO) calculations can be used to analyse the nature of the binding interactions of the fragment hits for the selection of fragments for evolution, merging and linking in order to optimize the chance of success.