Structure-based drug design strategies in medicinal chemistry

A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of\ud leads, as well as to accelerate the development of high quality drug candidates. Structure-based drug design (SBDD)\ud methods are becoming increasingly powerful, versatile and more widely used. This review summarizes current\ud developments in structure-based virtual screening and receptor-based pharmacophores, highlighting achievements as well\ud as challenges, along with the value of structure-based lead optimization, with emphasis on recent examples of successful\ud applications for the identification of novel active compounds.CNPqFAPES

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

Irish Area Section (Protein Interactions in Biology) Interactions of aminoglycoside antibiotics with rRNA

Abstract Aminoglycoside antibiotics are protein synthesis inhibitors applied to treat infections caused mainly by aerobic Gram-negative bacteria. Due to their adverse side effects they are last resort antibiotics typically used to combat pathogens resistant to other drugs. Aminoglycosides target ribosomes. We describe the interactions of aminoglycoside antibiotics containing a 2-deoxystreptamine (2-DOS) ring with 16S rRNA. We review the computational studies, with a focus on molecular dynamics (MD) simulations performed on RNA models mimicking the 2-DOS aminoglycoside binding site in the small ribosomal subunit. We also briefly discuss thermodynamics of interactions of these aminoglycosides with their 16S RNA target

Design, Synthesis, and Evaluation of Small Molecules in the Discovery of Novel Antimicrobial Agents

The increasing prevalence of antibiotic-resistant bacteria, including Mycobacterium tuberculosis, Streptococcus pneumoniae, Staphylococcus aureus, and Enterococcus faecalis, pushes us to discover new antibacterial agents to maintain adequate patient coverage. This body of work highlights the use of medicinal chemistry methodologies that encompass cross-disciplinary fields of study. Chapter 1 gives an introduction to the antibacterial drug targets, resistance, and how scientists are working to overcome obstacles encountered with drug-resistant bacteria. It also details modern medicinal chemistry applications in antimicrobial drug discovery. Chapter 2 details the use of a structure-guided library approach to drug design, in which large virtual libraries against the target are generated and filtered, based on pharmacophoric and structural constraints, to produce smaller and more structurally complex libraries prioritized for synthesis. In this work, bi-aryl sulfonamide libraries using contemporary medicinal chemistry techniques were synthesized as potential inhibitors of Mycobacterium tuberculosis cell wall biosynthesis via the rhamnose pathway. Chapter 3 describes the discovery of novel inhibitors of the PlsX/PlsY pathway to phosphatidic acid, a key intermediate in the biosynthesis of phospholipids in Gram-positive bacteria. Substrate mimics, incorporating various bioisosteric replacement head groups, were discovered demonstrating good enzyme inhibition and good antimicrobial activity against clinically relevant bacteria. Finally, Chapter 4 provides an overall discussion of the work detailed in this dissertation and future directions that will continue the advancement of these projects

DEVELOPMENT AND APPLICATIONS OF THE HINT FORCEFIELD IN PREDICTION OF ANTIBIOTIC EFFLUX AND VIRTUAL SCREENING FOR ANTIVIRALS

This work was aimed at developing novel tools that utilize HINT, an empirical forcefield capable of quantitating both hydrophobic and hydrophilic (hydropathic) interactions, for implementation in theoretical biology and drug discovery/design. The role of hydrophobicity in determination of macromolecular structure and formation of complexes in biological molecules is undeniable and has been the subject of research across several decades. Hydrophobicity is introduced, with a review of its history and contemporary theories. This is followed by a description of various methods that quantify this all-pervading phenomenon and their use in protein folding and contemporary drug design projects – including a detailed overview of the HINT forcefield. The specific aim of this dissertation is to introduce our attempts at developing new methods for use in the study of antibacterial drug resistance and antiviral drug discovery. Multidrug efflux is commonly regarded as a fast growing problem in the field of medicine. Several species of microbes are known to have developed resistance against almost all classes of antibiotics by various modes-of-action, which include multidrug transporters (a.k.a. efflux pumps). These proteins are present in both gram-positive and gram-negative bacteria and extrude molecules of various classes. They protect the efflux pump-expressing bacterium from harmful effects of exogenous agents by simply evacuating the latter. Perhaps the best characterized mechanism amongst these is that of the AcrA-AcrB-TolC efflux pump. Data is available in literature and perhaps also in proprietary databases available with pharmaceutical companies, characterizing this pump in terms of the minimum inhibitory concentration ratios (MIC ratios) for various antibiotics. We procured a curated dataset of 32 β-lactam and 12 antibiotics of other classes from this literature. Initial attempts at studying the MIC ratios of β-lactam antibiotics as a function of their three dimensional topology via 3D-quantitative structure activity relationship (3D-QSAR) technology yielded seemingly good models. However, this methodology is essentially designed to address single receptor-ligand interactions. Molecules being transported by the efflux pump must undoubtedly be involved in multiple interactions with the same. Notably, such methods require a pharmacophoric overlap of ligands prior to the generation of models, thereby limiting their applicability to a set of structurally-related compounds. Thus, we designed a novel method that takes various interactions between antibiotic agents and the AcrA-AcrB-TolC pump into account in conjunction with certain properties of the drugs. This method yielded mathematical models that are capable of predicting high/low efflux with significant efficiency (\u3e93% correct). The development of this method, along with the results from its validation, is presented herein. A parallel aim being pursued by us is to discover inhibitors for hemagglutinin-neuraminidase (HN) of human parainfluenza virus type 3 (HPIV3) by in silico screening. The basis for targeting HN is explored, along with commentary on the methodology adopted during this effort. This project yielded a moderate success rate of 34%, perhaps due to problems in the computational methodology utilized. We highlight one particular problem – that of emulating target flexibility – and explore new avenues for overcoming this obstacle in the long run. As a starting point towards enhancing the tools available to us for virtual screening in general (and for discovering antiviral compounds in specific), we explored the compatibility between sidechain rotamer libraries and the HINT scoring function. A new algorithm was designed to optimize amino acid residue sidechains, if provided with the backbone coordinates, by generating sidechain positions using the Dunbrack and Cohen backbone-dependent rotamer library and scoring them with the HINT scoring function. This rotamer library was previously used by its developers previously to design a very successful sidechain optimization algorithm called SCWRL. Output structures from our algorithm were compared with those from SCWRL and showed extraordinary similarities as well as significant differences, which are discussed herein. This successful implementation of HINT in our sidechain optimization algorithm establishes the compatibility between this forcefield and sidechain rotamer libraries. Future aims in this project include enhancement of our current algorithm and the design of a new algorithm to explore partial induced-fit in targets aimed at improving current docking methodology. This work shows significant progress towards the implementation of our hydropathic force field in theoretical modeling of biological systems in order to enhance our ability to understand atomistic details of inter- and intramolecular interactions which must form the basis for a wide variety of biological phenomena. Such efforts are key to not only to understanding the said phenomena, but also towards a solid basis for efficient drug design in the future

Computational approaches guiding for the design and optimization of novel chemo-types endowed with F508del-CFTR modulator ability

To date, monotherapy with VX-809 (Lumacaftor) or VX-770 (Ivacaftor) has not resulted in obvious clinical benefits for CF patients, while their combination regimen has provided positive results, stabilizing disease progress. Consequently, therapy combined with dual modulators or triple combination represents today the most promising prospect for developing new therapies. In this context, the research group in which I have been carrying out this thesis has dealt with rational design and computational studies of CFTR modulators during the past few years. The information obtained from our previous studies allowed us to proceed with the rational design and to predict the possible corrective activity of a new series of compounds with an aminoarylthiazole structure (AAT)1.,165. The previously proposed studies' reliability was supported by biological studies carried out on the newly synthesized molecules in collaboration with the research group led by Dr. Nicoletta Pedemonte (Istituto Giannina Gaslini, Genoa), verifying the corrective activity for F508del-CFTR of the newly designed derivatives. About the computational approaches so far applied, a QSAR model has been developed on the correctors available in literature guiding the following design and synthesis of hybrids compounds. This ligand-based method was used to overcome the paucity of information regarding a single and specific mechanism of action responsible for the corrective activity of VX-809. Indeed, as described in the literature, several hypotheses suggest multiple sites on the CFTR protein to which VX-809 could bind, first of all, the NBD1 domain. This thesis deepened the structure-based approach concerning various correctors described in the literature, including the hybrids developed by the present research group. In this context, experimental but partial data of the NBD1 domain of F508del-CFTR (PDB code: 4WZ6) were considered to perform molecular docking simulations of the compounds mentioned above. This research has been completed by molecular docking calculations performed on a whole model of the F508del-CFTR protein, which has been built in silico by our research group. Unlike what occurs for CFTR correctors, applying structure-based methods in the rational design of potentiators appears to be a more straightforward strategy since the experimental data concerning the binding mode of the VX-770 potentiator has recently become available (PDB code = 6O2P) and GLP1837 (PDB code = 6O1V). Starting from these assumptions, in this thesis, several libraries of compounds, described in the literature as CFTR potentiators, such as indoles, pyrazolquinolines, thienopyranes, cyanoquinolines, and AAT, have been studied to perform molecular docking studies and QSAR analysis activities. These approaches allowed us to obtain information to guide the rational design and future synthesis of new CFTR modulators. The research activity's further goal was to apply - in parallel to the studies just mentioned - ligand-based drug design analysis, using classical QSAR type analysis. This approach made it possible to overcome any limitation related to uniquely examining a single possible target for CFTR modulators and focusing on chemical scaffolds known today as correctors or potentiators

Design, Synthesis, And Evaluation Of Molecular Inhibitors For Biologically Relevant Enzymes

The work in this thesis details the design, synthesis, and biological evaluation of molecular inhibitors for the inhibition of biologically relevant enzymes. The first three chapters of this thesis concern the polyphenol resveratrol and its inhibition of the quinone reductase 2 (QR2) enzyme. The work on this subject resulted in the complete design, synthesis, biological and structural evaluation of a second generation library of resveratrol analogues. From this work we identified a novel resveratrol analogue that inhibits QR2 in a previously unknown binding orientation. The fourth chapter of this thesis details the de novo design of molecules for the inhibition of the Class II HMGR enzyme. The work on this subject involved the de novo design and in silico screening of a set of phenothiazine molecules for the inhibition of II-HMGR. These molecules were synthesized and assayed against II-HMGR, resulting in the identification of a substituted phenothiazine compound found to inhibit II-HMGR with an IC50 of 130 µM. This work resulted in a successful strategy for the identification of II-HMGR inhibitors

Bioinformatics Analysis and Modelling of Therapeutically Relevant Molecules

Ph.DDOCTOR OF PHILOSOPH

Text-basierte Ähnlichkeitssuche zur Treffer- und Leitstruktur-Identifizierung

This work investigated the applicability of global pairwise sequence alignment to the detection of functional analogues in virtual screening. This variant of sequence comparison was developed for the identification of homologue proteins based on amino acid or nucleotide sequences. Because of the significant differences between biopolymers and small molecules several aspects of this approach for sequence comparison had to be adapted. All proposed concepts were implemented as the ‘Pharmacophore Alignment Search Tool’ (PhAST) and evaluated in retrospective experiments on the COBRA dataset in version 6.1. The aim to identify functional analogues raised the necessity for identification and classification of functional properties in molecular structures. This was realized by fragment-based atom-typing, where one out of nine functional properties was assigned to each non-hydrogen atom in a structure. These properties were pre-assigned to atoms in the fragments. Whenever a fragment matched a substructure in a molecule, the assigned properties were transferred from fragment atoms to structure atoms. Each functional property was represented by exactly one symbol. Unlike amino acid or nucleotide sequences, small drug-like molecules contain branches and cycles. This was a major obstacle in the application of sequence alignment to virtual screening, since this technique can only be applied to linear sequences of symbols. The best linearization technique was shown to be Minimum Volume Embedding. To the best of knowledge, this work represents the first application of dimensionality reduction to graph linearization. Sequence alignment relies on a scoring system that rates symbol equivalences (matches) and differences (mismatches) based on functional properties that correspond to rated symbols. Existing scoring schemes are applicable only to amino acids and nucleotides. In this work, scoring schemes for functional properties in drug-like molecules were developed based on property frequencies and isofunctionality judged from chemical experience, pairwise sequence alignments, pairwise kernel-based assignments and stochastic optimization. The scoring system based on property frequencies and isofunctionality proved to be the most powerful (measured in enrichment capability). All developed scoring systems performed superior compared to simple scoring approaches that rate matches and mismatches uniformly. The frameworks proposed for score calculations can be used to guide modifications to the atom-typing in promising directions. The scoring system was further modified to allow for emphasis on particular symbols in a sequence. It was proven that the application of weights to symbols that correspond to key interaction points important to receptor-ligand-interaction significantly improves screening capabilities of PhAST. It was demonstrated that the systematic application of weights to all sequence positions in retrospective experiments can be used for pharmacophore elucidation. A scoring system based on structural instead of functional similarity was investigated and found to be suitable for similarity searches in shape-constrained datasets. Three methods for similarity assessment based on alignments were evaluated: Sequence identity, alignment score and significance. PhAST achieved significantly higher enrichment with alignment scores compared to sequence identity. p-values as significance estimates were calculated in a combination of Marcov Chain Monte Carlo Simulation and Importance Sampling. p-values were adapted to library size in a Bonferroni correction, yielding E-values. A significance threshold of an E-value of 1*10-5 was proposed for the application in prospective screenings. PhAST was compared to state-of-the-art methods for virtual screening. The unweighted version was shown to exhibit comparable enrichment capabilities. Compound rankings obtained with PhAST were proven to be complementary to those of other methods. The application to three-dimensional instead of two-dimensional molecular representations resulted in altered compound rankings without increased enrichment. PhAST was employed in two prospective applications. A screening for non-nucleoside analogue inhibitors of bacterial thymidin kinase yielded a hit with a distinct structural framework but only weak activity. The search for drugs not member of the NSAID (non-steroidal anti-inflammatory drug) class as modulators of gamma-secretase resulted in a potent modulator with clear structural distiction from the reference compound. The calculation of significance estimates, emphasizing on key interactions, the pharmacophore elucidation capabilities and the unique compound rannkings set PhAST apart from other screening techniques.In dieser Arbeit wurde die Anwendbarkeit von paarweisem globalen Sequenzalignment auf das Problem des Molekülsvergleichs im virtuellen Screening untersucht, einem Teilgebiet der computerbasierten Wirkstoffentwicklung. Sequenzalignment wurde zur Identifizierung homologer Proteine entwickelt. Bisher wurde es nur angewendet auf Sequenzen aus Aminosäuren oder Nukleotiden. Aufgrund der Unterschiede zwischen Biopolymeren und wirkstoffartigen Molekülen wurde dieser Ansatz zum Sequenzvergleich modifiziert und auf die konkrete Problemstellung angepasst. Alle vorgestellten und untersuchten Methoden wurden implementiert unter dem Namen ‚Pharmacophore Alignment Search Tool’ (PhAST). Zielsetzung bei der Entwicklung von PhAST war es, die funktionelle Ähnlichkeit zwischen Molekülen zu berechnen. Dafür war es notwendig, einen Ansatz zu implementieren, der den Atomen eines Moleküls funktionelle Eigenschaften zuweist. Dies wurde realisiert durch eine auf Fragmenten basierende Atomtypisierung. Den Atomen einer Sammlung vordefinierter Fragmente wurden nach bestem Wissen und Gewissen Eigenschaften zugewiesen. In jedem Fall, in dem eines der Fragmente als Substruktur eines Moleküls auftrat, wurden die Atomtypisierungen von dem jeweiligen Fragment auf die Atome des Moleküls übertragen. Insgesamt unterscheidet PhAST neun funktionelle Eigenschaften und deren Kombination, wobei jedem Atomtyp genau ein Symbol zugeordnet ist. Im Gegensatz zu Sequenzen von Aminosäuren und Nukleotiden sind wirkstoffartige Moleküle verzweigt, ungerichtet und enthalten Ringeschlüsse. Sequenzalignment ist aber ausschließlich auf lineare Sequenzen anwendbar. Folglich mussten Moleküle mit ihren funktionellen Eigenschaften zunächst in einer linearisierten Form gespeichert werden. Es wurde gezeigt, dass Minimum Volume Embedding die performanteste der getesteten Linearisierungsmethoden war. Nach bestem Wissen und Gewissen wurden in dieser Arbeit zum ersten mal Methoden zur Dimensionsreduktion auf das Problem der kanonischen Indizierung von Graphen angewendet. Zur Berechnung von Sequenzalignments ist ein Bewertungssystem von Equivalenzen und Unterschieden von Symbolen notwendig. Die bestehenden Systeme sind nur anwendbar auf Aminosäuren und Nukleotide. Daher wurde ein Bewertungssystem für Atomeigenschaften nach chemischer Intuition entwickelt, sowie drei automatisierte Methoden, solche Systeme zu berechnen. Das nach chemischer Intuition erstellte Bewertungsschema wurde als den anderen signifikant überlegen identifiziert. Die Flexibilität des Bewertungssystems in globalem Sequenzalignment machte es möglich, Symbole die berechneten Alignments stärker beeinflussen zu lassen, von denen bekannt war, dass sie für essentielle Wechselwirkungen in der Rezeptor-Ligand-Interaktion stehen. Es wurde gezeigt, dass diese Gewichtung die Screening Fähigkeiten von PhAST signifikant steigerte. Weiterhin konnte gezeigt werden, dass PhAST mit der systematischen Anwendung von Gewichten auf alle Sequenzpositionen in der Lage war, essentielle Wechselwirkungen für die Rezeptor-Ligand-Interaktion zu identifizieren. Bedingung hierfür war jedoch, dass ein geeigneter Datensatz mit aktiven und inaktiven Substanzen zur Verfügung stand. In dieser Arbeit wurden verschiedene Methoden evaluiert, mit denen aus Alignments Ähnlichkeiten berechnet werden können: Sequenzidentität, Alignment Score und p-Werte. Es wurde gezeigt, dass der Alignmentscore der Sequenzidentität für die Verwendung in PhAST signifikant überlegen ist. Für die Berechnung von p-Werten zur Bestimmung der Signfifikanz von Alignments musste zunächst die Verteilung von Alignment Scores für zufällige Sequenzen bestimmter Längen bestimmt werden. Dies geschah mit einer Kombination aus ‚Marcov Chain Monte Carlo Simulation’ und ‚Importance Sampling’. Die berechneten p-Werte wurden einer Bonferroni Korrektur unterzogen, und so unter Berücksichtigung der Gesamtzahl von im virtuellen Screening verglichenen Molekülen zu E-Werten. Als Ergebnis dieser Arbeit wird ein E-Wert von 1*10-5 als Grenzwert vorgeschlagen, wobei Alignments mit geringeren E-Werten als signifikant anzuerkennen sind. PhAST wurde in retrospektiven Screening mit anderen Methoden zum virtuellen Screening verglichen. Es konnte gezeigt werden, dass seine Fähigkeiten zur Identifizierung funktioneller Analoga mit denen der besten anderen Methoden vergleichbar oder ihnen sogar überlegen ist. Es konnte gezeigt werden, dass nach von PhAST berechneten Ähnlichkeiten sortierte Molekülsammlungen von den Sortierungen anderer Methoden abweichen. Im Rahmen dieser Arbeit wurde PhAST erfolgreich in zwei prospektiven Anwendungen eingesetzt. So wurde ein schwacher Inhibitor der bakteriellen Thymidinkinase identifiziert, der kein Nukleosid Analogon ist. In einem Screening nach Modulatoren der Gamma-Sekretase wurde ein potentes Molekül identifiziert, das deutliche strukturelle Unterschiede zur verwendeten Referenz aufwies

Novel antimicrobial peptides for enhanced antimicrobial activity against methicillin resistant Staphylococcus aureus: design, synthesis and formulation.

Doctoral Degree. University of KwaZulu-Natal, Durban.Abstract available in pdf