Solvated interaction energy: from small-molecule to antibody drug design

Scoring functions are ubiquitous in structure-based drug design as an aid to predicting binding modes and estimating binding affinities. Ideally, a scoring function should be broadly applicable, obviating the need to recalibrate and refit its parameters for every new target and class of ligands. Traditionally, drugs have been small molecules, but in recent years biologics, particularly antibodies, have become an increasingly important if not dominant class of therapeutics. This makes the goal of having a transferable scoring function, i.e., one that spans the range of small-molecule to protein ligands, even more challenging. One such broadly applicable scoring function is the Solvated Interaction Energy (SIE), which has been developed and applied in our lab for the last 15 years, leading to several important applications. This physics-based method arose from efforts to understand the physics governing binding events, with particular care given to the role played by solvation. SIE has been used by us and many independent labs worldwide for virtual screening and discovery of novel small-molecule binders or optimization of known drugs. Moreover, without any retraining, it is found to be transferrable to predictions of antibody-antigen relative binding affinities and as accurate as functions trained on protein-protein binding affinities. SIE has been incorporated in conjunction with other scoring functions into ADAPT (Assisted Design of Antibody and Protein Therapeutics), our platform for affinity modulation of antibodies. Application of ADAPT resulted in the optimization of several antibodies with 10-to-100-fold improvements in binding affinity. Further applications included broadening the specificity of a single-domain antibody to be cross-reactive with virus variants of both SARS-CoV-1 and SARS-CoV-2, and the design of safer antibodies by engineering of a pH switch to make them more selective towards acidic tumors while sparing normal tissues at physiological pH

Molecular dynamics and virtual screening approaches in drug discovery

Computer-aided drug discovery (CADD) methods are now routinely used in the preclinical phase of drug development. Powerful high-performance computing facilities and the extremely fast CADD methods constantly scale up the coverage of drug-like chemical space achievable in rational drug development. In this thesis, CADD approaches were applied to address several early-phase drug discovery problems. Namely, small molecule binding site detection on a novel target protein, virtual screening (VS) of molecular databases, and characterization of small molecule interactions with metabolic enzymes were studied. Various CADD methods, including molecular dynamics (MD) simulations in mixed solvents, molecular docking, and binding free energy calculations, were employed. Co-solvent MD simulations detected biologically relevant binding sites and provided guidance for screening potential protein-protein interaction inhibitors for a crucial protein of the SARS-CoV-2. VS with fragment- and negative image-based (F-NIB) models identified three active and structurally novel inhibitors of the putative drug target phosphodiesterase 10A. MD simulations and docking provided detailed insights on the effects of active site structural flexibility and variation on the binding and resultant metabolism of small molecules with the cytochrome P450 enzymes. The results presented in this thesis contribute to the increasing evidence that supports employment and further development of CADD approaches in drug discovery. Ultimately, rational drug development coupled with CADD may enable higher quality drug candidates to the human studies in the future, reducing the risk of financially and temporally costly clinical failure. KEYWORDS: Structure-based drug development, Computer-aided drug discovery (CADD), Molecular dynamics (MD) simulation, Virtual screening (VS), Fragmentand negative image-based (F-NIB) model, Structure-activity relationship (QSAR), Cytochrome P450 ligand binding predictionMolekyylidynamiikka- ja virtuaaliseulontamenetelmät lääkeaine-etsinnässä Tietokoneavusteista lääkeaine-etsintää käytetään nykyisin yleisesti prekliinisessä lääketutkimuksessa. Suurteholaskenta ja äärimmäisen nopeat tietokoneavusteiset lääkeaine-etsintämenetelmät mahdollistavat jatkuvasti kattavamman lääkkeenkaltaisten molekyylien kemiallisen avaruuden seulonnan. Tässä väitöskirjassa tietokonepohjaisia menetelmiä hyödynnettiin lääketutkimuksen prekliiniseen vaiheeseen liittyvissä tyypillisissä tutkimusongelmissa. Työhön kuului pienmolekyylien sitoutumisalueiden tunnistus uuden kohdeproteiinin rakenteesta, molekyylitietokantojen virtuaaliseulonta sekä pienmolekyylien ja metabolian entsyymien välisten vuorovaikutusten tietokonemallinnus. Työssä käytettiin useita tietokoneavusteisen lääkeaine-etsinnän menetelmiä, sisältäen molekyylidynamiikkasimulaatiot (MD-simulaatiot) vaihtuvissa liuottimissa, molekulaarisen telakoinnin ja sitoutumisenergian laskennan. Orgaanisen liuottimen ja veden sekoituksessa tehdyt MD-simulaatiot tunnistivat biologisesti merkittäviä sitoutumisalueita SARS-CoV-2:n tärkeästä proteiinista ja ohjasivat infektioon liittyvän proteiini-proteiinivuorovaikutuksen potentiaalisten estäjien etsintää. Virtuaaliseulonnalla tunnistettiin kolme rakenteellisesti uudenlaista tunnetun lääkekehityskohteen, fosfodiesteraasi 10A:n, estäjää hyödyntäen fragmentti- ja negatiivikuvamalleja. MD-simulaatiot ja telakointi tuottivat yksityiskohtaista tietoa sytokromi P450 entsyymien aktiivisen kohdan rakenteen jouston ja muutosten vaikutuksesta pienmolekyylien sitoutumiseen ja metaboliaan. Tämän väitöskirjan tulokset tukevat kasvavaa todistusaineistoa tietokoneavusteisen lääkeaine-etsinnän käytön ja kehityksen hyödyllisyydestä prekliinisessä lääketutkimuksessa. Tietokoneavusteinen lääkeaine-etsintä voi lopulta mahdollistaa korkeampilaatuisten lääkekandidaattien päätymisen ihmiskokeisiin, pienentäen taloudellisesti ja ajallisesti kalliin kliinisen tutkimuksen epäonnistumisen riskiä. AVAINSANAT: Rakennepohjainen lääkeainekehitys, Tietokoneavusteinen lääkeaine-etsintä, Molekyylidynamiikkasimulaatio (MD-simulaatio), Virtuaaliseulonta, Fragmentti- ja negatiivikuvamalli, Rakenne-aktiivisuussuhde, Sytokromi P450 ligandien sitoutumisen ennustu

Improving Docking Performance Using Negative Image-Based

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases

Structure-based Inhibitor Design for the Antimalarial Target Plasmepsin

Malaria stellt eine der weltweit am weitesten verbreiteten Krankheiten dar und ist nach Tuberkulose und AIDS die bedrohlichste aller Infektionskrankheiten. Heute gibt es eine Reihe von Medikamenten, die auf unterschiedliche Weise gegen Malaria wirken. Durch aufkommende Resistenzentwicklungen in vielen Regionen gegenüber zahlreichen Wirkstoffen, ist es jedoch notwendig geworden, neue Arzneimittel zu entwickeln. Durch die Sequenzierung des Plasmodium falciparum Genoms wurden die Plasmepsine, die Hauptgegenstand dieser Arbeit waren, als neue potentielle Zielstrukturen identifiziert. Zu Beginn der Arbeit waren bereits eine Reihe potenter, peptidomimetischer Inhibitoren und eine Kokristallstruktur von Plasmepsin II in Komplex mit Pepstatin A in der Literatur beschrieben. Um einen Beitrag im Bereich des strukturbasierten Designs von Plasmepsin Inhibitoren leisten zu können, wurden zunächst die erforderlichen Rahmenbedingungen geschaffen. Dazu gehörte die Etablierung eines Expressionssystems für Plasmepsin II und IV, was im Rahmen einer vorausgegangenen Diplomarbeit geschah. Während der Doktorarbeit ist es gelungen einen Assay zu entwickeln, der die Gesetze der Michaelis-Menten Kinetik befolgt. Weiterhin wurde versucht, ein funktionsfähiges Kristallisationssystem für Plasmespin II zu entwickeln, das die Aufklärung von Protein-Ligand-Bindungsmoden mittels Röntgenbeugungsexperimenten ermöglichen sollte. Obwohl die Reproduktion der in der Literatur bekannten Kristallstruktur mit Pepstatin A gelang, erwies es sich im Verlauf der Arbeit als schwierig, Kristalle des Zielproteins in Komplex mit neuartigen Inhibitoren zu erhalten. Nach Etablierung der für das strukturbasierte Liganden-Design erforderlichen Methoden galt es in Zusammenarbeit mit synthetisch arbeitenden Gruppen, Inhibitoren mit neuartigen, nichtpeptidomimetischen Eigenschaften zu entwerfen und zu optimieren. Erste Modelling-Studien ergaben, dass 2,3,4,7-Tetrahydro-1H-Azepin ein geeignetes Grundgerüst für die Entwicklung von Plasmepsin II und IV Inhibitoren darstellen könnte. Durch eine Kombination aus einer Datenbankanalyse mit dem Programm Cavbase und einem kombinatorischen Docking mit FlexXC wurden erste Liganden vorgeschlagen, die sich im Enzymassay als Hemmstoffe für Plasmepsin II und IV mit Ki-Werten im niedrig mikromolaren Bereich erwiesen. Eine ausgiebige Analyse theoretisch möglicher Wechselwirkungen zum Protein führte zu Vorschlägen für weitere Inhibitoren, wodurch die Affinitätsdaten bis in den nanomolaren Bereich verbessert werden konnten. Insgesamt standen die experimentell bestimmten Ki Werte von 13 Inhibitoren gut im Einklang mit der Design Hypothese und die beobachteten Struktur-Wirkbeziehungen stützen dabei den vorhergesagten Bindungsmodus. In einem weiteren Ansatz wurden Pyrrolidin Derivate, die ursprünglich als HIV-1 Protease Inhibitoren synthetisiert wurden, auf Plasmepsin-Hemmung getestet. In der Literatur sind einige Fälle beschrieben, bei denen HIV-1 Protease Inhibitoren gleichzeitig gute Hemmstoffe für Plasmepsine darstellen. Von insgesamt zwölf Molekülen zeigten die affinsten Liganden Ki Werte im nanomolaren Bereich. Für zwei Verbindungsklassen (Pyrrolidin-diol-diester und Pyrrolidindiamide) gelang es, plausible Bindungsmoden zu generieren. Mit den vorhandenen kristallographischen Informationen war es jedoch nicht möglich, einen sinnvollen Bindungsmodus für Pyrrolidindimethylenediamin-Derivate, die die dritte Verbindungsklasse darstellen, vorherzusagen. Da die Plasmepsine als sehr flexible Proteine bekannt sind, wurden Moleküldynamik (MD) Simulationen durchgeführt und mobile Bereiche innerhalb der Bindetasche genauer untersucht. Unter Berücksichtigung der Ergebnisse der MD Simulation konnte so ein Bindungsmodus für den Typ der Pyrrolidindimethylenediamin-Derivate erzeugt werden. Auch bei der Affinitätsdaten-Analyse einer Norstatin-Bibliothek, bei der die Verbindungen sich nur im P1-Substituenten unterschieden, konnten zunächst überraschende Ergebnisse mit Hilfe der MD Simulation erklärt werden. Eine konformative Öffnung der Plasmepsin II S1 Tasche wurde beobachtet, wodurch eine Anpassung an sperrige P1 Substituenten ermöglicht wird. So wurden durch die durchgeführte MD Simulation zahlreiche Erkenntnisse gewonnen, die von Relevanz für das strukturbasierte Wirkstoffdesign sind. Ausgehend von den Azepin Derivaten wurde in dieser Arbeit ein dritter Ansatz verfolgt, Plasmepsin Inhibitoren mit neuartigen Grundgerüsten zu entwickeln. Zu diesem Zweck wurde Ftrees (Feature Trees) verwendet, ein Computerprogramm, das durch seine Funktionsweise einen Übergang von einem Suchmolekül zu strukturell unähnlichen Molekülen „Scaffold Hopping“ ermöglichen soll. Eine Verbindung mit einem Thiophengrundgerüst fiel bei der Auswertung als besonders interessant auf und wurde auf die Plasmepsine getestet. Anfängliche Ki Werte im zweistellig mikromolaren Bereich konnten durch gezieltes Design um den Faktor 110 verbessert werden, was zu ersten Inhibitoren im nanomolaren Bereich führte. Insgesamt gelang es in dieser Arbeit durch unterschiedliche Ansätze Hemmstoffe für Plasmepsin II und IV vorherzusagen, bei denen die Struktur-Wirkbeziehungen mit den erzeugten Bindungsmoden weitestgehend übereinstimmten. Strukturlösungsversuche gelangen nur mit Pepstatin A, Moleküldynamiksimulationen gewährten dennoch einen Einblick in die hohe Flexibilität und stabile Konformationen der Plasmepsine. Daraus wurden Erkenntnisse für das strukturbasierte Wirkstoffdesign gewonnen, was zur Entwicklung neuer Malaria-Medikamente einen Beitrag leisten könnte

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs

Theoretical screening of organic conjugated materials

As the urgency to address the effects of climate change increases, so does the need to discover new materials for the generation of renewable energy, to replace the environmentally dam- aging combustion of fossil fuels. Two main areas of research are focused on the design and discovery of photoactive materials for photovoltaics and for photocatalysts for water splitting. Although there are currently high-efficiency photovoltaics commercially available, there is mo- tivation to replace them with materials with non-toxic and earth-abundant compositions. As they generally meet these criteria, organic conjugated materials are very desirable candidates for these applications. Computational chemistry methods can accelerate materials discovery, eliminating the need to synthesize large libraries of molecules in the preliminary screening stages. Both high-accuracy, expensive methods and fast, cheap, lower-accuracy methods have their merits and in conjunction with one another can provide a detailed and informative description of chemical systems. The high-throughput virtual screening methodology used throughout this thesis provides the opportunity to efficiently explore property space and high- light potential candidates for given applications, such as polymeric photocatalysts, organic photovoltaics and dye sensitizers in solar cells. In this thesis this methodology is explored for a small aromatic molecules, diketopyrrolopyrrole-based dyes and both ordered and disordered polymers. Through the high-throughput virtual screening, large datasets of chemical com- pounds were investigated and analysed, highlighting the patterns in the optical and electronic properties influenced by building block sequence, conformerism and composition. The use of high-accuracy, expensive methods is also explored in this thesis, demonstrating the difficulties in pushing such methods to larger chemical structures

IN SILICO METHODS FOR DRUG DESIGN AND DISCOVERY

Computer-aided drug design (CADD) methodologies are playing an ever-increasing role in drug discovery that are critical in the cost-effective identification of promising drug candidates. These computational methods are relevant in limiting the use of animal models in pharmacological research, for aiding the rational design of novel and safe drug candidates, and for repositioning marketed drugs, supporting medicinal chemists and pharmacologists during the drug discovery trajectory.Within this field of research, we launched a Research Topic in Frontiers in Chemistry in March 2019 entitled “In silico Methods for Drug Design and Discovery,” which involved two sections of the journal: Medicinal and Pharmaceutical Chemistry and Theoretical and Computational Chemistry. For the reasons mentioned, this Research Topic attracted the attention of scientists and received a large number of submitted manuscripts. Among them 27 Original Research articles, five Review articles, and two Perspective articles have been published within the Research Topic. The Original Research articles cover most of the topics in CADD, reporting advanced in silico methods in drug discovery, while the Review articles offer a point of view of some computer-driven techniques applied to drug research. Finally, the Perspective articles provide a vision of specific computational approaches with an outlook in the modern era of CADD

Computational methods applied to drug discovery: the rational design of dual inhibitors of FAAH and COX

The search for effective and safe drugs in pain-relief treatment represents a great challenge for medicinal chemists. Lipid derived mediators, such as endocannabinoids, may have different roles as agonists of cannabinoid receptors, relieving pain, or as substrates of cyclooxygenase (COX), generating the pro-inflammatory prostamides. Moreover, the tissue-protective endocannabinoid anandamide is metabolised by fatty acid amide hydrolase (FAAH). Therefore, a new challenging approach in pain-relief might be the development of dual action FAAH/COX inhibitors. The purpose of this thesis is to apply computational methods in drug discovery to assist medicinal chemistry studies targeting the rational design of novel FAAH/COX inhibitors, and to exploit structural studies relative to two side projects on other biological targets. The wider project of this thesis explores the mechanism of action and the rational design of novel FAAH/COX dual inhibitors. The reversible mixed type inhibitors Flu-AM1 and Ibu-AM5, derivatives of flurbiprofen and ibuprofen, respectively, retain similar COX inhibitory properties and are more potent FAAH inhibitors than the parent compounds. Applying a combination of molecular docking, MD simulations and free energy evaluation of the ligand-receptor complex, the binding mode of the enantiomer forms of Flu-AM1 and Ibu-AM5 has been found in the substrate access channel of FAAH and has been supported by studies of site-directed mutagenesis. The substitution of the isobutyl group of Ibu-AM5 with 4-(2-(trifluoromethyl)pyridin-4-yl)amino group led to the design of TPA5 derivative, which showed an inhibitory activity (IC50 = 0.59 μM) similar to the lead compound (Ibu-AM5, IC50 = 0.52 μM). Kinetic studies of TPA5 revealed that it is a pure competitive inhibitor of rat FAAH and molecular modeling studies supported a binding mode that overlap the anandamide analog MAFP. Among TPA5 derivatives, compound TPA27 exhibited a 10-fold enhancement in the inhibitory profile against FAAH (IC50 = 0.058 μM). Thermodynamic Integration calculations performed to complete the transformation of TPA5 in TPA27 yielded a free energy difference of 0.3 kcal/mol, which indicates a slight lower affinity of TPA27 with respect to TPA5, in the competitive binding site. Kinetics studies showed that TPA27 could be considered the first non-competitive reversible FAAH inhibitor reported so far, and that it more likely binds to an allosteric site. Differences in the inhibitory potency against rat and mouse FAAH for all compounds studied suggested different aminoacid composition of both competitive and non-competitive binding sites. This information was used as criteria of selection for a putative allosteric site found between the cytosolic port and the interface of the FAAH monomers. Computational studies in the allosteric site allowed the definition of the binding mode of Ibu-AM5 and TPA27. Nevertheless, a series of derivatives of Ibu-AM5 and Flu-AM1 were designed in order to get more information on the structure-activity relationships, leading to the identification of novel derivatives with improved activity against FAAH (Ibu-AM56, IC50 = 0.08 μM; Ibu-AM57, IC50 = 0.1 μM; Flu-AM3, IC50 = 0.02 μM. Finally, the thesis also reports the results of two other projects: i) the design of potential anticancer peptides that interfere in the formation of the tetrameric complex hUbA1/UbcH10/Ub2, key intermediate of the ubiquitination cascade.; ii) structural studies on the hybridization of PNA of different length with miR-509-3p, involved in regulating the expression of the CFTR gene, as a way to validate a potential new strategy for the treatment of Cystic Fibrosis

Do All Roads Really Lead to Rome? Learnings from Comparative Analysis using SPR, NMR, & X-Ray Crystallography to Optimize Fragment Screening in Drug Discovery.

There are several biophysical methods developed to rapidly identify weakly binding fragments to a target protein. X-ray crystallography provides structural information that is crucial for fragment optimization, however there are several criteria that must be met for a successful fragment screening including the production of soakable and well-diffracting crystals. Therefore, having a reliable cascade of screening methods to be used as pre-screens prior to labor-intensive X-ray crystallography would be extremely beneficial. This would allow the filtering of compounds as the screening progresses so that only the most promising hits remain. But which method should be the one to start the screening cascade? In this work, various sets of fragment libraries were screened against three different proteins; namely tRNA guanine transglycosylase (TGT) an important protein in Shigella, membrane associated protein peroxin 14 (PEX14) of T. Brucei, and endothiapepsin (EP), to investigate whether different screening methods will reveal similar collections of putative binders. The detailed comparative analysis of the findings obtained by the different methods is discussed in this thesis. Shigellosis, an acute bacterial infection of the intestine, is caused by the gram-negative Shigella bacterium whose pathogenicity is reliant on virulence factors (VirF) required to invade epithelial cells. The expression of these VirF is modulated by TGT. Strategies developed to inhibit TGT include potent active-site inhibitors to block the binding of tRNA, thereby preventing the transcription of the virulence factors. Our 96-fragment library was screened against TGT using SPR, NMR, and X-ray crystallography, as described in Chapter 2. A total of 81 fragments were screened in SPR using a direct binding assay approach, revealing a hit rate of 12%. A total of 77 fragments were screened in NMR revealing a hit rate of 29%. High-resolution crystal structures were also collected for the entire fragment library by soaking, revealing a hit rate of 8%. Upon comparison of all discovered fragment hits no overlaps from all three methods were found. Several factors are responsible for this finding such as exclusion of fragments from individual screens due to technical reasons. In detail, four X-ray hits were excluded from the SPR and NMR screens, two SPR hits were discarded from the NMR screen, and five NMR hits were never subjected to the SPR screen. SPR and NMR are currently the most commonly applied primary fragment screening techniques, however, our results suggest that if they would have been applied as incipient methods of a screening cascade, they would have missed three binders discovered by a subsequently applied, more elaborate crystallographic screen. X-ray crystallography allows the detection of specific binders that may be too weak binders to be detected by SPR and even by NMR but can still provide valid structural information to support the search for appropriate starting points in lead discovery. Additionally, MD simulations of the apo wild type TGT have predicted the opening of a transient sub-pocket located above the guanine/preQ1 pocket, which suggested a strategy to target this new binding site for the design of new inhibitors against TGT following a structure- based drug design concept which is also discussed in section 2.3. The human African trypanosomiasis (HAT), also known as the sleeping sickness, is a vector-borne parasitic disease caused by T. brucei and transmitted to humans by bites of the tsetse fly. T. brucei lacks feedback allosteric regulation of early steps in glycolysis but compartmentalizes the relevant enzymes within organelles called glycosomes. PEX14, a peroxin protein essential for biogenesis of glycosomes, forms an important protein-protein interaction with PEX5, an import receptor that transports cytoplasmic glycosomal enzymes into the organelle. Disrupting the PEX14/PEX5 interaction leads to the accumulation of glycosomal enzymes in the cytosol, depletion of ATP, glucose toxicity, metabolic collapse and death of T. brucei. This disruption can be achieved through small molecules that bind to and block PEX14, preventing PEX5 binding. A previous NMR screening of a fragment library resulted in fragment hits that bind to the N-terminal domain (NTD) of T. brucei PEX14. In this project, we attempted to validate these hits through X-ray crystallography by soaking, to allow visualization of the fragment interactions. The promising fragment hits would then be optimized into more potent lead compounds. Crystallization of the NTD PEX14 with a mutation in the first residue (E1W) revealed blocked binding pockets, as described in Chapter 3. The purpose of the added tryptophan was to render fluorescent properties to the short NTD construct which lacked fluorescent amino acids. However, this tryptophan was found to block the binding pockets of its neighboring crystal mates in the protein crystal, rendering a crystal form impossible to use for soaking. Attempts to find new crystal forms with free pockets were unsuccessful, as the small size of the protein and the hydrophobic nature of tryptophan rendered tightly packed protein crystals that block the binding pockets of neighboring crystal mates. Virtual Screening to discover novel ligands for co-crystallization revealed a ligand that aids the crystallization of the E1W PEX14 variant in the same space group but with a slightly different packing. This produced a crystal form that proved successful for fragment soaking as it enabled the binding of two additional fragment hits binding to further protein pockets. Additionally, the wild type form of PEX14 which lacks the tryptophan residue and thus has free binding pockets was crystallized. This enabled the soaking of a previously designed lead compound in different pockets of the PEX5 binding site. By obtaining a crystal structure of this complex at a resolution of 1.8 Å, the feasibility of using wild type PEX14 crystals for further fragment screening has been demonstrated. Endothiapepsin is a member of the pepsin-like aspartic proteases responsible for the hydrolytic cleavage of peptide substrates. Owing to its high degree of similarity to other pharmacologically relevant aspartic proteases, it has served as the model enzyme for studying their mechanism and to discover first lead structures. In previous work done by other members from our group to identify and characterize endothiapepsin binders, X-ray crystallography was consulted as a primary fragment screening method and its hit identification potential was compared to several biochemical and biophysical screening methods. The fragment library screened was designed for general purposes and contained 361 entries. Comparison of the overlap in the hit rates of the different methods to that of X-ray crystallography revealed a low overlap, with the RDA having the highest overlap at 7% and MS having the lowest overlap at 1% followed by STD NMR at 3%. To understand the reason behind the low overlap, two of these screening techniques were prioritized for closer analysis as described in Chapter 4. The 71 X-ray detected fragment hits were selected and rescreened again with STD NMR under slightly different buffer conditions, in addition to WaterLOGSY NMR experiments. The second STD NMR screen detected almost double the amount of hits as the initial one, and the Water LOGSY screen had the highest correlation from the NMR methods to the X-ray hits at 69%. This comparative analysis also revealed the phenomena of active site fragment displacement by use of so-called reporter ligands and that non-deuterated water in STD NMR may lead to false negatives. The entire 361 fragment library was also screened with SPR using an inhibition in solution assay, adding another biophysical method for our comparative analysis to give us further insight of which conditions are crucial to maintain while transferring across different techniques. The resulting hit rate from SPR was 34%, correlating to an overlap of 11% with the X-ray hits - the highest correlation between screening methods reported by us thus far. Finally, we also studied fragment detection and cocktailing in crystallography in comparison to fragment cocktailing in NMR. From this we concluded that cocktailing in crystallography can also lead to false negatives due to fragment competitive behavior and can reveal a different binding mode for a given fragment compared to the adopted geometry found when soaked individually. As for NMR, despite the ability to detect competitive binding of fragments due to the temporary binding and unbinding events, the parallel binding and thus detection of fragments is not always guaranteed as seen in 20% of the fragments we screened, in addition to our observation that the detection of fragments in cocktail NMR may also depend on the comparison of the cocktail set they are a part of