The Development and Applications of the HINT Scoring Function: Exploring Colchicine-Site Anticancer Agents and Tautomerism

The overall aim of this work was to apply HINT, an empirical scoring function based on the understanding of hydrophobicity, to analyze and predict the binding affinities and biological activities of colchicine-site anticancer agents. The second, concurrent aim was to improve the scoring function by incorporating tautomerism within the modeling process. Our belief is that proper evaluation of tautomeric forms for small molecules will improve performance of virtual screening. The novel pyrrole-based compounds targeting the colchicine site were docked into the receptor using HINT as a rescoring function. Two distinct binding modes dictated by the size and shape of a subpocket were predicted to differentiate the highly active compounds from the weak ones. Of the residues predicted to participate in binding for the active binding mode, Cys241β was revealed to form a weak but critical hydrogen bond with the ligand. A larger collection of colchicine-site agents, biologically tested in the same laboratory including our pyrrole-based compounds were subject to 3D quantitative structure-activity relationship (QSAR) study. Using results on docking the pyrrole compounds as a guide, relative binding poses and QSAR models were built to facilitate ligand design and optimization. A new 3D modeling approach was introduced to visually highlight the unique features of highly active compounds and the commonality of all compounds in the dataset using HINT maps and successfully tested on the colchicine-site agents. These results will provide valuable guidance in the future design and development of new colchicine-site agents. To incorporate tautomerism within HINT, we proposed and developed two workflow approaches: a general search tool using a simple and intuitive algorithm analyzing hydrogen shift patterns to identify and enumerate tautomeric structures, and a database that contains commonly observed tautomeric structures. The first approach was designed for small-scale docking studies and the second approach was designed for large-scale virtual screening. The tautomer module in HINT will give more accurate modeling results when the compound encountered is able to tautomerize

Computational Deorphaning of <em>Mycobacterium tuberculosis</em> Targets

Tuberculosis (TB) continues to be a major health hazard worldwide due to the resurgence of drug discovery strains of Mycobacterium tuberculosis (Mtb) and co-infection. For decades drug discovery has concentrated on identifying ligands for ~10 Mtb targets, hence most of the identified essential proteins are not utilised in TB chemotherapy. Here computational techniques were used to identify ligands for the orphan Mtb proteins. These range from ligand-based and structure-based virtual screening modelling the proteome of the bacterium. Identification of ligands for most of the Mtb proteins will provide novel TB drugs and targets and hence address drug resistance, toxicity and the duration of TB treatment

Computational de-orphaning of Mycobacterium tuberculosis targets

Tuberculosis (TB) continues to be a major health hazard worldwide due to the resurgence of drug discovery strains of Mycobacterium tuberculosis (Mtb) and co-infection. For decades drug discovery has concentrated on identifying ligands for ~10 Mtb targets, hence most of the identified essential proteins are not utilised in TB chemotherapy. Here computational techniques were used to identify ligands for the orphan Mtb proteins. These range from ligand-based and structure-based virtual screening modelling the proteome of the bacterium. Identification of ligands for most of the Mtb Proteins will provide novel TB drugs and targets and hence address drug resistance, toxicity and the duration of TB treatment

Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening

Virtual screening of large compound databases, looking for potential ligands of a target protein, is a major tool in computer-aided drug discovery. Throughout the years, different techniques such as similarity searching, pharmacophore matching, or molecular docking have been applied with the aim of finding hit compounds showing appreciable affinity. Molecular dynamics simulations in mixed solvents have been shown to identify hot spots relevant for protein-drug interaction, and implementations based on this knowledge were developed to improve pharmacophore matching of small molecules, binding free-energy estimations, and docking performance in terms of pose prediction. Here, we proved in a retrospective manner that cosolvent-derived pharmacophores from molecular dynamics (solvent sites) improve the performance of docking-based virtual screening campaigns. We applied a biased docking scheme based on solvent sites to nine relevant target proteins that have a set of known ligands or actives and compounds that are, presumably, nonbinders (decoys). Our results show improvement in virtual screening performance compared to traditional docking programs both at a global level, with up to 35% increase in areas under the receiver operating characteristic curve, and in early stages, with up to a 7-fold increase in enrichment factors at 1%. However, the improvement in pose prediction of actives was less profound. The presented application makes use of the AutoDock Bias method and is the only cosolvent-derived pharmacophore technique that employs its knowledge both in the ligand conformational search algorithm and the final affinity scoring for virtual screening purposes.Fil: Arcon, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Defelipe, Lucas Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Lopez, Elias Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Burastero, Osvaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Modenutti, Carlos Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Barril, Xavier. Universidad de Barcelona; EspañaFil: Marti, Marcelo Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Turjanski, Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; Argentin

Discovery and development of novel inhibitors for the kinase Pim-1 and G-Protein Coupled Receptor Smoothened

Investigation of the cause of disease is no easy business. This is particularly so when one reflects upon the lessons taught us in antiquity. Prior to the beginning of the last century, diagnosis and treatment of diseases such as cancers was so bereft of hope that there was little physicians could offer in the way of comfort, let alone treatment. One of the major insights from investigations into cancers this century has been that those involved in research leading to treatments are not dealing with a singular malady but multiple families of diseases with different mechanisms and modes of action. Therefore, despite the end game being similar in cancers, that of uncontrolled growth and replication leading to cellular dysfunction, different diseases require different approaches in targeting them. This leads us to a particular broad treatment approach, that of drug design. A drug is, in the classical sense, a small molecule that, upon introduction into the body, interacts with biochemical targets to induce a wider biological effect, ideally with both an intended target and intended effect. The conceptual basis underpinning this `lock-and-key' paradigm was elucidated over a century ago and the primary occupation of those involved in biochemical research has been to determine as much information as possible about both of these protein locks and drug keys. And, as inferred from the paradigm, molecular shape is all-important in determining and controlling action against the most important locks with the most potent and specific keys. The two most important target classes in drug discovery for some time have been protein kinases and G Protein-Coupled Receptors (GPCRs). Both classes of proteins are large families that perform very different tasks within the body. Kinases activate and inactive many cellular processes by catalysing the transfer of a phosphate group from Adenosine Tri-Phosphate (ATP) to other targets. GPCRs perform the job of interacting with chemical signals and communicating them into a biological response. Dysfunction in both types of proteins in certain cells can lead to a loss of biological control and, ultimately, a cancer. Both of kinases and GPCRs have entirely different chemical structures so structural knowledge therefore becomes crucial in any approach targeting cells where dysfunction has occurred. Thus, for this thesis, a member from each class was investigated using a combination of structural approaches. From the kinase class, the kinase Proviral Integration site for MuLV (Pim-1) and from the GPCR class, the cell membrane-bound Smoothened receptor (SMO). The kinase \pimone\ was the target of various approaches in \autoref{chap:three}. Although a heavily studied target from the mid-2000's, there is a paucity of inhibitors targeting residues more remote from structural characteristics that define kinases. Further limiting extension possibilities is that \pimone\ is constitutively active so no inhibitors targeting an inactive state are possible. An initial project (\pone) used the known binding properties of small molecules, or, `fragments' to elucidate structural and dynamic information useful for targeting \pimone. This was followed by three projects, all with the goal of inhibitor discovery, all with different foci. In \ptwo, fragment binding modes from \pone\ provided the basis for the extension and development of drug-like inhibitors with a focus on synthetic feasibility. In contrast, inhibitors were found in \pthree\ via a large-scale public dataset of purchasable molecules that possess drug-like properties. Finally, \pfour\ took the truncated form of a particularly attractive fragment from \pone\ that was crystallised with \pimone, verified its binding mode and then generated extensions with, again, a focus on synthetic feasibility. The GPCR \smo\ has fewer molecular studies and much about its structural behaviour remains unknown. As the most `druggable' protein in the Hedgehog pathway, structural studies have primarily focussed on stabilising its inactive state to prevent signal transduction. Allied to this is that there are generally few inhibitors for \smo\ and the drugs for cancers related to its dysfunction are vulnerable to mutations that significantly reduce their effectiveness or abrogate it entirely. The elucidation of structural information in therefore of high priority. An initial study attempting to identify an unknown molecule from prior experiments led to insights regarding binding characteristics of specific moieties. This was particularly important to understand not just where favourable moieties bind but also sections of the \smo\ binding pocket with unfavourable binding. In both subsequent virtual screens performed in Chapter 4, the primary aim was to find new drug-like inhibitors of \smo\ using large public datasets of commercially-available molecules. The initial screen retrieved relatively few inhibitors so the binding pocket was modified to find a structural state more amenable to small molecule binding. These modifications led to a significant number of new, chemically novel inhibitors for \smo, some structural information useful for future inhibitors and the elucidation of structure-activity relationships useful for inhibitor design. This underpins the idea that structural information is of critical importance in the discovery and design of molecular inhibitors

Repurposing the trypanosomatidic gsk kinetobox for the inhibition of parasitic pteridine and dihydrofolate reductases

Three open-source anti-kinetoplastid chemical boxes derived from a whole-cell phenotypic screening by GlaxoSmithKline (Tres Cantos Anti-Kinetoplastid Screening, TCAKS) were exploited for the discovery of a novel core structure inspiring new treatments of parasitic diseases targeting the trypansosmatidic pteridine reductase 1 (PTR1) and dihydrofolate reductase (DHFR) enzymes. In total, 592 compounds were tested through medium-throughput screening assays. A subset of 14 compounds successfully inhibited the enzyme activity in the low micromolar range of at least one of the enzymes from both Trypanosoma brucei and Lesihmania major parasites (pan-inhibitors), or from both PTR1 and DHFR-TS of the same parasite (dual inhibitors). Molecular docking studies of the protein–ligand interaction focused on new scaffolds not reproducing the well-known antifolate core clearly explaining the experimental data. TCMDC-143249, classified as a benzenesulfonamide derivative by the QikProp descriptor tool, showed selective inhibition of PTR1 and growth inhibition of the kinetoplastid parasites in the 5 µM range. In our work, we enlarged the biological profile of the GSK Kinetobox and identified new core structures inhibiting selectively PTR1, effective against the kinetoplastid infectious protozoans. In perspective, we foresee the development of selective PTR1 and DHFR inhibitors for studies of drug combinations

Identification of a potential allosteric site of Golgi α-mannosidase II using computer-aided drug design

Golgi α-mannosidase II (GMII) is a glycoside hydrolase playing a crucial role in the N-glycosylation pathway. In various tumour cell lines, the distribution of N-linked sugars on the cell surface is modified and correlates with the progression of tumour metastasis. GMII therefore is a possible molecular target for anticancer agents. Here, we describe the identification of a non-competitive GMII inhibitor using computer-aided drug design methods including identification of a possible allosteric binding site, pharmacophore search and virtual screening.publishedVersio