Identification of a novel scaffold for allosteric inhibition of wild type and drug resistant HIV-1 reverse transcriptase by fragment library screening

Targeting HIV-1 Reverse Transcriptase Using a Fragment-Based Approach

Human immunodeficiency virus type I (HIV-1) is a retrovirus that infects cells of the host's immune system leading to acquired immunodeficiency syndrome and potentially death. Although treatments are available to prevent its progression, HIV-1 remains a major burden on health resources worldwide. Continued emergence of drug-resistance mutations drives the need for novel drugs that can inhibit HIV-1 replication through new pathways. The viral protein reverse transcriptase (RT) plays a fundamental role in the HIV-1 replication cycle, and multiple approved medications target this enzyme. In this study, fragment-based drug discovery was used to optimize a previously identified hit fragment (compound B-1), which bound RT at a novel site. Three series of compounds were synthesized and evaluated for their HIV-1 RT binding and inhibition. These series were designed to investigate different vectors around the initial hit in an attempt to improve inhibitory activity against RT. Our results show that the 4-position of the core scaffold is important for binding of the fragment to RT, and a lead compound with a cyclopropyl substitution was selected and further investigated. Requirements for binding to the NNRTI-binding pocket (NNIBP) and a novel adjacent site were investigated, with lead compound 27-a minimal but efficient NNRTI-offering a starting site for the development of novel dual NNIBP-Adjacent site inhibitors.

Implications of Fragment-Based Drug Discovery in Tuberculosis and HIV

Tuberculosis (TB) remains a global health problem and the emergence of HIV has further worsened it. Long chemotherapy and the emergence of drug-resistance strains of Mycobacterium tuberculosis as well as HIV has aggravated the problem. This demands urgent the need to develop new anti-tuberculosis and antiretrovirals to treat TB and HIV. The lack of diversity in drugs designed using traditional approaches is a major disadvantage and limits the treatment options. Therefore, new technologies and approaches are required to solve the current issues and enhance the production of drugs. Interestingly, fragment-based drug discovery (FBDD) has gained an advantage over high-throughput screenings as FBDD has enabled rapid and efficient progress to develop potent small molecule compounds that specifically bind to the target. Several potent inhibitor compounds of various targets have been developed using FBDD approach and some of them are under progression to clinical trials. In this review, we emphasize some of the important targets of mycobacteria and HIV. We also discussed about the target-based druggable molecules that are identified using the FBDD approach, use of these druggable molecules to identify novel binding sites on the target and assays used to evaluate inhibitory activities of these identified druggable molecules on the biological activity of the targets.

Genetic Mutations in the S-loop of Human Glutathione Synthetase: Links Between Substrate Binding, Active Site Structure and Allostery

The second step in the biosynthesis of the cellular antioxidant glutathione (GSH) is catalyzed by human glutathione synthetase (hGS), a negatively cooperative homodimer. Patients with mutations in hGS have been reported to exhibit a range of symptoms from hemolytic anemia and metabolic acidosis to neurological disorders and premature death. Several patient mutations occur in the S-loop of hGS, a series of residues near the negatively cooperative γ-GC substrate binding site. Experimental point mutations and molecular dynamic simulations show the S-loop not only binds γ-GC through a salt bridge and multiple hydrogen bonds, but the residues also modulate allosteric communication in hGS. By elucidating the role of S-loop residues in active site structure, substrate binding, and allostery, the atomic level sequence of events that leads to the detrimental effects of hGS mutations in patients are more fully understood.

Critical Evaluation of Native Electrospray Ionization Mass Spectrometry for Fragment-Based Screening

Fragment-based screening presents a promising alternative to high-throughput screening and has gained great attention in recent years. So far, only a few studies have discussed mass spectrometry as a screening technology for fragments. Herein, we report the application of native electrospray ionization mass spectrometry (MS) for screening defined sets of fragments against four different target proteins. Fragments were selected from a primary screening conducted with a thermal shift assay (TSA) and represented different binding categories. Our data indicated that, beside specific complex formation, many fragments show extensive multiple binding and also charge-state shifts. Both of these factors complicate automated data analysis and decrease the attractiveness of native MS as a primary screening tool for fragments. A comparison of the hits identified by native MS and TSA showed good agreement for two of the proteins. Furthermore, we discuss general challenges, including the determination of an optimal fragment concentration and the question of how to rank fragment hits according to their affinity. In conclusion, we consider native MS to be a highly valuable tool for the validation and deeper investigation of promising fragment hits rather than a method for primary screening.

Analysis of drug-endogenous human metabolite similarities in terms of their maximum common substructures

In previous work, we have assessed the structural similarities between marketed drugs (‘drugs’) and endogenous natural human metabolites (‘metabolites’ or ‘endogenites’), using ‘fingerprint’ methods in common use, and the Tanimoto and Tversky similarity metrics, finding that the fingerprint encoding used had a dramatic effect on the apparent similarities observed. By contrast, the maximal common substructure (MCS), when the means of determining it is fixed, is a means of determining similarities that is largely independent of the fingerprints, and also has a clear chemical meaning. We here explored the utility of the MCS and metrics derived therefrom. In many cases, a shared scaffold helps cluster drugs and endogenites, and gives insight into enzymes (in particular transporters) that they both share. Tanimoto and Tversky similarities based on the MCS tend to be smaller than those based on the MACCS fingerprint-type encoding, though the converse is also true for a significant fraction of the comparisons. While no single molecular descriptor can account for these differences, a machine learning-based analysis of the nature of the differences (MACCS_Tanimoto vs MCS_Tversky) shows that they are indeed deterministic, although the features that are used in the model to account for this vary greatly with each individual drug. The extent of its utility and interpretability vary with the drug of interest, implying that while MCS is neither ‘better’ nor ‘worse’ for every drug–endogenite comparison, it is sufficiently different to be of value. The overall conclusion is thus that the use of the MCS provides an additional and valuable strategy for understanding the structural basis for similarities between synthetic, marketed drugs and natural intermediary metabolites.

MetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous Metabolites

BACKGROUND

Previous studies compared the molecular similarity of marketed drugs and endogenous human metabolites (endogenites), using a series of fingerprint-type encodings, variously ranked and clustered using the Tanimoto (Jaccard) similarity coefficient (TS). Because this gives equal weight to all parts of the encoding (thence to different substructures in the molecule) it may not be optimal, since in many cases not all parts of the molecule will bind to their macromolecular targets. Unsupervised methods cannot alone uncover this. We here explore the kinds of differences that may be observed when the TS is replaced-in a manner more equivalent to semi-supervised learning-by variants of the asymmetric Tversky (TV) similarity, that includes α and β parameters.

RESULTS

Dramatic differences are observed in (i) the drug-endogenite similarity heatmaps, (ii) the cumulative "greatest similarity" curves, and (iii) the fraction of drugs with a Tversky similarity to a metabolite exceeding a given value when the Tversky α and β parameters are varied from their Tanimoto values. The same is true when the sum of the α and β parameters is varied. A clear trend toward increased endogenite-likeness of marketed drugs is observed when α or β adopt values nearer the extremes of their range, and when their sum is smaller. The kinds of molecules exhibiting the greatest similarity to two interrogating drug molecules (chlorpromazine and clozapine) also vary in both nature and the values of their similarity as α and β are varied. The same is true for the converse, when drugs are interrogated with an endogenite. The fraction of drugs with a Tversky similarity to a molecule in a library exceeding a given value depends on the contents of that library, and α and β may be "tuned" accordingly, in a semi-supervised manner. At some values of α and β drug discovery library candidates or natural products can "look" much more like (i.e., have a numerical similarity much closer to) drugs than do even endogenites.

CONCLUSIONS

Overall, the Tversky similarity metrics provide a more useful range of examples of molecular similarity than does the simpler Tanimoto similarity, and help to draw attention to molecular similarities that would not be recognized if Tanimoto alone were used. Hence, the Tversky similarity metrics are likely to be of significant value in many general problems in cheminformatics.

Anti-HIV Drug Discovery and Development: Current Innovations and Future Trends

The early effectiveness of combinatorial antiretroviral therapy (cART) in the treatment of HIV infection has been compromised to some extent by rapid development of multidrug-resistant HIV strains, poor bioavailability, and cumulative toxicities, and so there is a need for alternative strategies of antiretroviral drug discovery and additional therapeutic agents with novel action modes or targets. From this perspective, we first review current strategies of antiretroviral drug discovery and optimization, with the aid of selected examples from the recent literature. We highlight the development of phosphate ester-based prodrugs as a means to improve the aqueous solubility of HIV inhibitors, and the introduction of the substrate envelope hypothesis as a new approach for overcoming HIV drug resistance. Finally, we discuss future directions for research, including opportunities for exploitation of novel antiretroviral targets, and the strategy of activation of latent HIV reservoirs as a means to eradicate the virus.

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities

INTRODUCTION

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery.

AREAS COVERED

In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress.

EXPERT OPINION

Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Multiple ligand detection and affinity measurement by ultrafiltration and mass spectrometry analysis applied to fragment mixture screening

Binding affinity of a small molecule drug candidate to a therapeutically relevant biomolecular target is regarded the first determinant of the candidate's efficacy. Although the ultrafiltration-LC/MS (UF-LC/MS) assay enables efficient ligand discovery for a specific target from a mixed pool of compounds, most previous analysis allowed for relative affinity ranking of different ligands. Moreover, the reliability of affinity measurement for multiple ligands with UF-LC/MS has hardly been strictly evaluated. In this study, we examined the accuracy of K(d) determination through UF-LC/MS by comparison with classical ITC measurement. A single-point K(d) calculation method was found to be suitable for affinity measurement of multiple ligands bound to the same target when binding competition is minimized. A second workflow based on analysis of the unbound fraction of compounds was then developed, which simplified sample preparation as well as warranted reliable ligand discovery. The new workflow implemented in a fragment mixture screen afforded rapid and sensitive detection of low-affinity ligands selectively bound to the RNA polymerase NS5B of hepatitis C virus. More importantly, ligand identification and affinity measurement for mixture-based fragment screens by UF-LC/MS were in good accordance with single ligand evaluation by conventional SPR analysis. This new approach is expected to become a valuable addition to the arsenal of high-throughput screening techniques for fragment-based drug discovery.

Identification of mechanistically distinct inhibitors of HIV-1 reverse transcriptase through fragment screening

Fragment-based screening methods can be used to discover novel active site or allosteric inhibitors for therapeutic intervention. Using saturation transfer difference (STD) NMR and in vitro activity assays, we have identified fragment-sized inhibitors of HIV-1 reverse transcriptase (RT) with distinct chemical scaffolds and mechanisms compared to nonnucleoside RT inhibitors (NNRTIs) and nucleoside/nucleotide RT inhibitors (NRTIs). Three compounds were found to inhibit RNA- and DNA-dependent DNA polymerase activity of HIV-1 RT in the micromolar range while retaining potency against RT variants carrying one of three major NNRTI resistance mutations: K103N, Y181C, or G190A. These compounds also inhibit Moloney murine leukemia virus RT but not the Klenow fragment of Escherichia coli DNA polymerase I. Steady-state kinetic analyses demonstrate that one of these fragments is a competitive inhibitor of HIV-1 RT with respect to deoxyribonucleoside triphosphate (dNTP) substrate, whereas a second compound is a competitive inhibitor of RT polymerase activity with respect to the DNA template/primer (T/P), and consequently also inhibits RNase H activity. The dNTP competing RT inhibitor retains activity against the NRTI-resistant mutants K65R and M184V, demonstrating a drug resistance profile distinct from the nucleotide competing RT inhibitors indolopyridone-1 (INDOPY-1) and 4-dimethylamino-6-vinylpyrimidine-1 (DAVP-1). In antiviral assays, the T/P competing compound inhibits HIV-1 replication at a step consistent with an RT inhibitor. Screening of additional structurally related compounds to the three fragments led to the discovery of molecules with improved potency against HIV-1 RT. These fragment inhibitors represent previously unidentified scaffolds for development of novel drugs for HIV-1 prevention or treatment.

The role of strong electrostatic interactions at the dimer interface of human glutathione synthetase

The obligate homodimer human glutathione synthetase (hGS) provides an ideal system for exploring the role of protein-protein interactions in the structural stability, activity and allostery of enzymes. The two active sites of hGS, which are 40 Å apart, display allosteric modulation by the substrate γ-glutamylcysteine (γ-GC) during the synthesis of glutathione, a key cellular antioxidant. The two subunits interact at a relatively small dimer interface dominated by electrostatic interactions between S42, R221, and D24. Alanine scans of these sites result in enzymes with decreased activity, altered γ-GC affinity, and decreased thermal stability. Molecular dynamics simulations indicate these mutations disrupt interchain bonding and impact the tertiary structure of hGS. While the ionic hydrogen bonds and salt bridges between S42, R221, and D24 do not mediate allosteric communication in hGS, these interactions have a dramatic impact on the activity and structural stability of the enzyme.

A ligand-observed mass spectrometry approach integrated into the fragment based lead discovery pipeline

In fragment-based lead discovery (FBLD), a cascade combining multiple orthogonal technologies is required for reliable detection and characterization of fragment binding to the target. Given the limitations of the mainstream screening techniques, we presented a ligand-observed mass spectrometry approach to expand the toolkits and increase the flexibility of building a FBLD pipeline especially for tough targets. In this study, this approach was integrated into a FBLD program targeting the HCV RNA polymerase NS5B. Our ligand-observed mass spectrometry analysis resulted in the discovery of 10 hits from a 384-member fragment library through two independent screens of complex cocktails and a follow-up validation assay. Moreover, this MS-based approach enabled quantitative measurement of weak binding affinities of fragments which was in general consistent with SPR analysis. Five out of the ten hits were then successfully translated to X-ray structures of fragment-bound complexes to lay a foundation for structure-based inhibitor design. With distinctive strengths in terms of high capacity and speed, minimal method development, easy sample preparation, low material consumption and quantitative capability, this MS-based assay is anticipated to be a valuable addition to the repertoire of current fragment screening techniques.

Increasing chemical space coverage by combining empirical and computational fragment screens

Most libraries for fragment-based drug discovery are restricted to 1,000-10,000 compounds, but over 500,000 fragments are commercially available and potentially accessible by virtual screening. Whether this larger set would increase chemotype coverage, and whether a computational screen can pragmatically prioritize them, is debated. To investigate this question, a 1281-fragment library was screened by nuclear magnetic resonance (NMR) against AmpC β-lactamase, and hits were confirmed by surface plasmon resonance (SPR). Nine hits with novel chemotypes were confirmed biochemically with KI values from 0.2 to low mM. We also computationally docked 290,000 purchasable fragments with chemotypes unrepresented in the empirical library, finding 10 that had KI values from 0.03 to low mM. Though less novel than those discovered by NMR, the docking-derived fragments filled chemotype holes from the empirical library. Crystal structures of nine of the fragments in complex with AmpC β-lactamase revealed new binding sites and explained the relatively high affinity of the docking-derived fragments. The existence of chemotype holes is likely a general feature of fragment libraries, as calculation suggests that to represent the fragment substructures of even known biogenic molecules would demand a library of minimally over 32,000 fragments. Combining computational and empirical fragment screens enables the discovery of unexpected chemotypes, here by the NMR screen, while capturing chemotypes missing from the empirical library and tailored to the target, with little extra cost in resources.

Substrate deconstruction and the nonadditivity of enzyme recognition

Predicting substrates for enzymes of unknown function is a major postgenomic challenge. Substrate discovery, like inhibitor discovery, is constrained by our ability to explore chemotypes; it would be expanded by orders of magnitude if reactive sites could be probed with fragments rather than fully elaborated substrates, as is done for inhibitor discovery. To explore the feasibility of this approach, substrates of six enzymes from three different superfamilies were deconstructed into 41 overlapping fragments that were tested for activity or binding. Surprisingly, even those fragments containing the key reactive group had little activity, and most fragments did not bind measurably, until they captured most of the substrate features. Removing a single atom from a recognized substrate could often reduce catalytic recognition by 6 log-orders. To explore recognition at atomic resolution, the structures of three fragment complexes of the β-lactamase substrate cephalothin were determined by X-ray crystallography. Substrate discovery may be difficult to reduce to the fragment level, with implications for function discovery and for the tolerance of enzymes to metabolite promiscuity. Pragmatically, this study supports the development of libraries of fully elaborated metabolites as probes for enzyme function, which currently do not exist.

Kinetic characterization of fragment binding in AmpC β-lactamase by high-throughput molecular simulations

Small molecules used in fragment-based drug discovery form multiple, promiscuous binding complexes difficult to capture experimentally. Here, we identify such binding poses and their associated energetics and kinetics using molecular dynamics simulations on AmpC β-lactamase. Only one of the crystallographic binding poses was found to be thermodynamically favorable; however, the ligand shows several binding poses within the pocket. This study demonstrates free-binding molecular simulations in the context of fragment-to-lead development and its potential application in drug design.

Identification of inhibitors of the antibiotic-resistance target New Delhi metallo-β-lactamase 1 by both nanoelectrospray ionization mass spectrometry and ultrafiltration liquid chromatography/mass spectrometry approaches

Mass spectrometry-based platforms have gained increasing success in discovery of ligands bound to therapeutic targets as drug candidates. We established both a nanoelectrospray ionization mass spectrometry (nanoESI-MS) assay and an ultrafiltration liquid chromatography/mass spectrometry (LC/MS) assay to identify new ligands for New Delhi metallo-β-lactamase 1 (NDM-1), responsible for worldwide antibiotic resistance. To alleviate nonspecific binding of hydrophobic compounds and eliminate false positives typically encountered in the indirect LC/MS-based assay, we introduced a blocking protein in the control, which remarkably enhances the selectivity and accuracy of the indirect approach. Side-by-side comparison of the two MS-based approaches for the first time further reveals unique advantages of the indirect approach, including better reproducibility and tolerance of interference. Moreover, the success of fishing out a potent ligand from a mixture of small-molecule fragments demonstrates great potential of the indirect LC/MS-based approach for constructing a robust screening platform against combinatorial libraries or natural product extracts. More importantly, by combining the results of MS-based analyses, enzymatic activity assay, competition experiments, and structural simulation, we discovered a new compound as a promising drug candidate targeting NDM-1.

Detecting allosteric sites of HIV-1 reverse transcriptase by X-ray crystallographic fragment screening

HIV-1 reverse transcriptase (RT) undergoes a series of conformational changes during viral replication and is a central target for antiretroviral therapy. The intrinsic flexibility of RT can provide novel allosteric sites for inhibition. Crystals of RT that diffract X-rays to better than 2 Å resolution facilitated the probing of RT for new druggable sites using fragment screening by X-ray crystallography. A total of 775 fragments were grouped into 143 cocktails, which were soaked into crystals of RT in complex with the non-nucleoside drug rilpivirine (TMC278). Seven new sites were discovered, including the Incoming Nucleotide Binding, Knuckles, NNRTI Adjacent, and 399 sites, located in the polymerase region of RT, and the 428, RNase H Primer Grip Adjacent, and 507 sites, located in the RNase H region. Three of these sites (Knuckles, NNRTI Adjacent, and Incoming Nucleotide Binding) are inhibitory and provide opportunities for discovery of new anti-AIDS drugs.

In silico deconstruction of ATP-competitive inhibitors of glycogen synthase kinase-3β

Fragment-based methods have emerged in the last two decades as alternatives to traditional high throughput screenings for the identification of chemical starting points in drug discovery. One arguable yet popular assumption about fragment-based design is that the fragment binding mode remains conserved upon chemical expansion. For instance, the question of the binding conservation upon fragmentation of a molecule is still unclear. A number of papers have challenged this hypothesis by means of experimental techniques, with controversial results, "underlining" the idea that a simple generalization, maybe, is not possible. From a computational standpoint, the issue has been rarely addressed and mostly to test novel protocols on limited data sets. To fill this gap, we here report on a computational retrospective study concerned with the in silico deconstruction of leadlike compounds, active on the pharmaceutically relevant enzyme glycogen synthase kinase-3β.

Biophysical and computational fragment-based approaches to targeting protein-protein interactions: applications in structure-guided drug discovery

Drug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein-protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids - so-called hotspots - may contribute the majority of interaction-free energy. The challenges posed by protein-protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein-protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods - nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry - to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates that target protein-protein interactions and have therapeutic value.

Structural biology and drug discovery for protein-protein interactions

Although targeting protein-protein interfaces of regulatory multiprotein complexes has become a significant focus in drug discovery, it continues to pose major challenges. Most interfaces would be classed as 'undruggable' by conventional analyses, as they tend to be large, flat and featureless. Over the past decade, encouragement has come from the discovery of hotspots that contribute much of the free energy of interaction, and this has led to the development of tethering methods that target small molecules to these sites, often inducing adaptive changes. Equally important has been the recognition that many protein-protein interactions involve a continuous epitope of one partner and a well-defined groove or series of specific small pockets. These observations have stimulated the development of stapled α-helical peptides and other proteomimetic approaches. They have also led to the realisation that fragments might gain low-affinity 'footholds' on some protein-protein interfaces, and that these fragments might be elaborated to useful modulators of the interactions.

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.

Emerging role of surface plasmon resonance in fragment-based drug discovery

Surface plasmon resonance (SPR) offers a method of biophysical fragment screening that is fast, efficient, cost effective and accurate. SPR is increasingly being adopted as a secondary assay to validate fragment hits. Recently, technical advances have resulted in the emergence of SPR as a primary screening methodology for fragment-based drug discovery. Moreover, SPR biosensor assays can be developed for a wide range of proteins, including membrane proteins, such as G-protein-coupled receptors. In this review, we discuss the advantages and limitations of SPR fragment screening including experimental consideration of reducing false positive and false negative rates to a minimum. We discuss how ligand efficiency can be used both as a method to eliminate false positives and to understand which fragments in a library may be a source of false negatives.

Deconstruction of non-nucleoside reverse transcriptase inhibitors of human immunodeficiency virus type 1 for exploration of the optimization landscape of fragments

This study has taken a closer look at the theoretical basis for protein-fragment interactions. The approach involved the deconstruction of 3 non-nucleoside inhibitors of HIV-1 reverse transcriptase and investigation of the interaction between 21 substructures and the enzyme. It focused on the concept of ligand efficiency and showed that ligand independent free energy fees (ΔG(ind)) are crucial for the understanding of the binding affinities of fragments. A value of 7.0 kcal mol(-1) for the ΔG(ind) term is shown to be a lower limit for the NNRTI binding pocket of HIV-1 RT. The addition of the ΔG(ind) term to the dissociation free energy in the calculation of a corrected ligand efficiency, in combination with the lack of an efficient ligand binding hot spot in the NNIBP, fully explains the existence of nonbinding NNRTI substructures. By applying the concept to a larger set of ligands, we could define a binding site profile that indicates the absence of an efficient fragment binding hot spot but an efficient binding of full-sized NNRTIs. The analysis explains some of the challenges in identifying fragments against flexible targets involving conformational changes and how fragments may be prioritized.

Fragment screening and HIV therapeutics

Fragment screening has proven to be a powerful alternative to traditional methods for drug discovery. Biophysical methods, such as X-ray crystallography, NMR spectroscopy, and surface plasmon resonance, are used to screen a diverse library of small molecule compounds. Although compounds identified via this approach have relatively weak affinity, they provide a good platform for lead development and are highly efficient binders with respect to their size. Fragment screening has been utilized for a wide range of targets, including HIV-1 proteins. Here, we review the fragment screening studies targeting HIV-1 proteins using X-ray crystallography or surface plasmon resonance. These studies have successfully detected binding of novel fragments to either previously established or new sites on HIV-1 protease and reverse transcriptase. In addition, fragment screening against HIV-1 reverse transcriptase has been used as a tool to better understand the complex nature of ligand binding to a flexible target.