Structural and dynamic analysis of wild and splice variants human µ-opiod receptors in complex with Morphine and IBNtxA and human topoisomerase II alpha mutational basis of Amsacrine resistance

Morphine prescribing is limited by its high addiction tendency and other serious effects. Recent animal’s biological studies on Mu 6TM splice variants, which mainly include G1, G2 and Mu3, supported a high safety and potency profiles of IBNtxA as potential alternative of Morphine. Nevertheless, there is no high-resolution structures of these 6TM variants, and the detailed structural features and dynamic characteristics of these splice variants remain elusive. We applied homology modeling and MD simulation to probe the structural, dynamic and ligand binding differences between the wild type (7TM) and two major truncated 6TM variants (G1 and G2). MD results underscored important structural and dynamic differences between these receptors as well as prioritized ligand affinity toward each receptor. The second project in this thesis involves in silico analysis of mutational basis of Amsacrine resistance. Both R487K and E571K mutations were studied. MD results indicated significant weakening of Amsacrine affinity in two mutants in a consistent manner with the previous biological degree of resistance of two mutants. Additionally, the intercalation loss and ligand ternary complex coordinate changes were also revealed by MD simulation as possible causes of resistance

Computational study targeting anti-fungal Tavaborole analogs and anti-cancer BRACO19

This thesis comprises of three computer aided drug design studies utilizing molecular docking and molecular dynamic simulations: (i) a lead optimization study virtually screening an initial library of ~120000 lead compounds targeting fungal leucyl tRNA synthetase, (ii) an exploratory study to understand the binding pathway of BRACO19 to a parallel telomeric DNA G-quadruplex by MD simulations and compare with experimentally solved X-ray crystal structure (iii) a comparative study to understand the lack of selectivity of BRACO19 to various topologies of human telomeric DNA G-quadruplex over DNA duplex. The first chapter provides the background information required to understand the molecular docking studies and molecular dynamics simulation (MD) studies conducted and discussed in this thesis. This introductory chapter is organized as follows: the first section is an introduction to molecular recognition in protein-ligand interactions, the second section introduces computer-aided drug design, the third section introduces homology modelling, the fourth section discusses molecular docking and virtual screening, the fifth section introduces methods for binding affinity prediction and the sixth section explains MD simulations. The second chapter of this thesis proposes a library of compounds with enhanced activity compared to the parent molecule it had been modified from. Tavaborole, the recently approved topological anti-fungal drug, inhibits leucyl tRNA synthetase by irreversible covalent bonding and hinders protein synthesis. The benzo-boroxole pharmacophore of tavaborole is responsible for its unique activity. This study theoretically proposes molecules with improved anti-fungal affinity. The third chapter of this thesis explores the binding pathway of anti-cancer drug, BRACO19 and human telomeric DNA G-quadruplex. G-quadruplex specific ligands that stabilizes the G-quadruplex, have great potential to be developed as anticancer agents. A free human telomeric DNA G-quadruplex and an unbound BRACO19 are simulated and the resulting structure is then compared with an experimentally solved X-ray structure of human telomeric G-quadruplex with a bound BRACO19 intercalated within the G-quadruplex. Three binding modes have been identified: top end stacking, bottom intercalation and groove binding. Bottom intercalation mode (51% of the population) is identical to the binding pose in the X-ray solved crystal structure. The fourth chapter of this thesis compares different topological folds of human telomeric DNA G-quadruplexes (parallel, antiparallel and hybrid) that have been experimentally solved using molecular dynamic simulation to understand the 62-fold preferential selectivity of BRACO19 towards human telomeric DNA G-quadruplex over DNA duplex. Groove binding mode was found to be the most stable binding mode for the duplex and top stacking mode for the G-quadruplexes. The non-existential binding selectivity of BRACO19 can be accounted to the similar groove binding to both the duplex and the G-quadruplex. For that reason, a modification should be induced such that this prospective ligand destabilizes binding to the duplex but stabilizes the G-quadruplex binding

Determination of in silico rules for predicting small molecule binding behavior to nucleic acids in vitro.

The vast knowledge of nucleic acids is evolving and it is now known that DNA can adopt highly complex, heterogeneous structures. Among the most intriguing are the G-quadruplex structures, which are thought to play a pivotal role in cancer pathogenesis. Efforts to find new small molecules for these and other physiologically relevant nucleic acid structures have generally been limited to isolation from natural sources or rationale synthesis of promising lead compounds. However, with the rapid growth in computational power that is increasingly becoming available, virtual screening and computational approaches are quickly becoming a reality in academia and industry as an efficient and economical way to discover new lead compounds. These computational efforts have historically almost entirely focused on proteins as targets and have neglected DNA. We present research here showing that not only can software be utilized for targeting DNA, but that selectivity metrics can be developed to predict the binding mechanism of a small molecule to a DNA target. The software Surflex and Autodock were chosen for evaluation and were demonstrated to be able to accurately reproduce the known crystal structures of several small molecules that bind by the most common nucleic acid interacting mechanisms of groove binding and intercalation. These software were further used to rationalize known affinity and selectivity data of a 67 compound library of compounds for a library of nucleic acid structures including duplex, triplex and quadruplexes. Based upon the known binding behavior of these compounds, in silica metrics were developed to classify compounds as either groove binders or intercalators. These rules were subsequently used to identify new triplex and quadruplex binding small molecules by structure and ligand-based virtual screening approaches using a virtual library consisting of millions of commercially available small molecules. The binding behavior of the newly discovered triplex and quadruplex binding compounds was empirically validated using a number of spectroscopic, fluorescent and thermodynamic equilibrium techniques. In total, this research predicted the binding behavior of these test compounds in silica and subsequently validated these findings in vitro. This research presents a novel approach to discover lead compounds that target multiple nucleic acid morphologies

A mechanical study of cancer drug-receptor interactions, specifically in G-Quadruplex DNA and Topoisomerase I enzymes

Computational methods are becoming essential in drug discovery as they provide information that traditional drug development methods lack. Using these methods to understand drug-receptor interactions in detail, researchers are able to efficiently design promising drug candidates. In this study, extra precision Glide docking, molecular dynamics simulations and MMGBSA binding energy calculations provided information about the binding behavior of small molecules to two specific targets for current cancer therapeutics: G-quadruplex DNA and Topoisomerase I enzyme. The first study focuses on the compound Telomestatin, which induces apoptosis of various cancer cells with a relatively low effect on somatic cells due to its high selectivity toward G-quadruplex over duplex DNA. Three major binding poses were discovered: top end stacking, bottom end stacking and a groove binding. A high resolution structure of this complex does not yet exist, so this is the first time Telomestatin binding modes have been reported. The second study focuses on 8 Camptothecin class Topoisomerase I inhibitors, which have been reported to effectively treat multiple types of cancer, however are limited by their drug resistance. Recent computational studies have indicated that the mutations near the active binding site of the drug can significantly weaken the drug binding and may be a major cause of the drug resistance. Here, a complete study of each Camptothecin analog in each mutated complex in the active binding site is presented. On this set of mutant complexes, Topotecan and Camptothecin have much smaller binding energy decrease than a set of new Camptopthcin derivatives (Lurtotecan, LESN-38, Gimatecan, Exatecan and Belotecan) currently under clinical trials. Lucanthone, a non-Camptothecin, shows comparable results to Topotecan and Camptothecin, indicating that it may exhibit the least drug resistance and is therefore a promising candidate for future studies as a Topoisomerase I inhibitor. In addition, a trend is observed from our binding energy data that the shorter the distance of a mutant to a ligand, the greater the decrease in binding energy (with one exception). The results found in each of these binding studies will be utilized to further advance effective cancer therapeutics in the future

Mapping biophysics through enhanced Monte Carlo techniques

This thesis is focused on the study of molecular interactions at the atomistic detail and is divided into one introductory chapter and four chapters referencing different problems and methodological approaches. All of them are focused on the development and improvement of computational Monte Carlo algorithms to study, in an efficient manner, the behavior of these systems at a classical molecular mechanics level. The four biophysical problems studied in this thesis are: induced fit docking between protein-ligand and between DNA-ligand to understand the binding mechanism, protein stretching response, and generation/ scoring of protein-protein docking poses. The thesis is organized as follows: First chapter corresponds to the state of the art in computational methods to study biophysical interactions, which is the starting point of this thesis. Our in-house PELE algorithm and the main standard methods such as molecular dynamics will be explained in detail. Chapter two is focused on the main PELE modifications to add new features, such as the addition of a new force field, implicit solvent and an anisotropic network specific for DNA simulation studies. We study, compare and validate the conformations generated by six representative DNA fragments with the new PELE features using molecular dynamics as a reference. Chapter three is devoted to applying the new methods implemented and tested in PELE to study protein-ligand interactions and DNA-ligand interactions using four systems. First, we study the porphyrin binding to Gun4 protein combining PELE and molecular dynamics simulations. Besides, we provide a docking pose that has been corroborated by a new crystal structure published during the revision process of the submitted study showing the accuracy of our predictions. In the second project, we use our improved version of PELE to generate the first structural model of an alpha glucose 1,6-bisphosphate substrate bound to the human Phosphomannomutase 2 demonstrating that this ligand can adopt two low-energy orientations. The third project is the study of DNA-ligand interactions for three cisplatin drugs where we evaluate the binding free energy using Markov state models. We show excellent results respect another free energy methods studied with molecular dynamics. The last project is the study of the daunomycin DNA intercalator where we simulate and study the binding process with PELE. Chapter four is focused on the computational study of force extension profiles during the protein unfolding. We added a dynamic harmonic constraint following a similar procedure applied in steered molecular dynamics to our Monte Carlo approach to fix or pull some selected atoms forcing the protein unfolding in a defined direction. We implement and compare with steered molecular dynamics this technique with Ubiquitin and Azurin proteins. Moreover, we add this feature to a well-known algorithm called MCPRO from William Jorgensen¿s group at YALE University to evaluate the free energy associated to the unfolding of the deca-alanine system. Chapter five corresponds to the introduction of a multiscale approach to study protein-protein docking. A coarse-grained model will be combined with a Monte Carlo exploration reducing the degrees of freedom to generate thousands of protein-protein poses in a quick way. Poses produced by this procedure will be refined and ranked through a protonation, hydrogen bond optimization, and minimization protocol at the all-atom representation to identify the best poses. I present two test cases where this procedure has been applied showing a good accuracy in the predictions: tryptogalinin and ferredoxin/flavodoxin systems.Aquesta tesi es centra en l'estudi de les interaccions moleculars amb detall atomic i es divideix en un capítol d'introducció i quatre capítols que fan referència a diferents problemes i enfocaments metodològics. Tots ells se centren en el desenvolupament i millora dels algoritmes computacionals de Monte Carlo per estudiar, de manera eficient, el comportament d'aquests sistemes a un nivell mecànica molecular clàssica. Els quatre problemes biofísics estudiats en aquesta tesi són: acoblament induït entre la proteïna-lligand i entre DNA-lligant per comprendre el mecanisme d'unió, resposta de les proteïnes a l'estirament, i la generació/puntuació d'acoblament entre poses proteïna-proteïna. La tesi s'organitza de la següent manera: El primer capítol correspon a l'estat de l'art en mètodes computacionals per estudiar les interaccions biofísiques, que és el punt de partida d'aquesta tesi. El nostre PELE algoritme i els principals mètodes estàndard com ara la dinàmica molecular s'explicaran en detall. El capítol dos es centra en les principals modificacions PELE per afegir noves característiques, com ara l'addició d'un nou camp de força, solvent implícit i modes normals per aquests estudis de simulació d'ADN. Es fa un estudi, comparació i validació de les conformacions generades per sis fragments d'ADN representatius amb PELE utilitzant dinàmica molecular com a referència. El tercer capítol està dedicat a l'aplicació dels nous mètodes implementats i provats en PELE per estudiar les interaccions proteïna-lligand i la interacció lligand-DNA utilitzant quatre sistemes. En primer lloc, se estudia la unió a proteïnes GUN4 combinant PELE i simulacions de dinàmica molecular. A més, es proposa un acoblament que ha sigut corroborat per una nova estructura cristal·lina publicada durant el procés de revisió de l'estudi mostrant l'exactitud de les nostres prediccions. En el segon projecte, hem utilitzat la nostra versió millorada de PELE per generar el primer model estructural d'una glucosa alfa substrat 1,6-bisfosfat unit a la fosfomanomutasa humana 2, que demostra que aquest lligant pot adoptar dues orientacions de baiza energia. El tercer projecte és l'estudi de les interaccions d'ADN lligant per tres medicaments cisplatí on se avalua l'energia lliure d'unió utilitzant Markov States Models. Es mostren excel·lents resultats respecte d'altres mètodes d'energia lliure estudiats amb dinàmica molecular. L'últim projecte és l'estudi de l'intercalador d'ADN anomenat daunomicina on es simula i estudia el procés d'unió amb PELE. El capítol 4 es centra en l'estudi computacional dels perfils d'extensió de la força durant el desplegament de la proteïna. Hem afegit una restricció harmònica dinàmica seguint un procediment similar al aplicat en dinàmica molecular en el nostre algoritme Monte Carlo per fixar o moure alguns àtoms seleccionats obligant a desplegar la proteïna en una direcció definida. Aquesta tècnica s'ha implementat i comparat amb dinàmica molecular per les proteïnes ubiquitina i azurin. D'altra banda, hem afegit aquesta modificació a un algoritme ben conegut anomenat MCPRO del grup de William Jorgensen a la Universitat de Yale per avaluar l'energia lliure associada al desplegament del sistema deca alanina. El capítol cinc correspon a la introducció d'un enfocament multiescala per estudiar l'acoblament proteïna-proteïna. Un model de gra gruixut es combinat amb una exploració Monte Carlo per reduir els graus de llibertat i generar milers de poses proteïna-proteïna d'una manera ràpida. Les poses produides per aquest procediment es perfeccionan i evaluan a través d'una protonació, optimització d'enllaços d'hidrogen, i minimització a escala atòmica per identificar les millors poses. Es presenten dos casos de prova on s'ha aplicat aquest procediment que mostra una bona precisió en les prediccions: tryptogalinin i ferredoxina / flavodoxina systems

Molecular mechanism, binding free energy, and sequence selectivity of intercalation of doxorubicin and DNA

Title from PDF of title page viewed December 17, 2021VitaIncludes bibliographical references (pages 128-147)Thesis (Ph.D.)--Department of Physics and Astronomy, School of Biological and Chemical Sciences. University of Missouri--Kansas City, 2021Dissertation advisor; Wai-Yim ChingMany drugs interact noncovalently with DNA either by groove binding or intercalation. Intercalation is a key process in drug discovery and biosensor development. Doxorubicin (DOX) is an intercalator drug that treats a wide range of cancers. However, its binding process with DNA is still a highly debatable topic on both the experimental and theoretical sides with many unanswered questions. Particularly, what is the key physical factor(s) that drives the complex formation at both conformational change and insertion binding stages? What are the DOX sequence-selectivity and the role of physical factors in determining this selectivity? What is the best model to describe the relationship between binding affinity and selectivity of an intercalator drug? How do the aqueous environment and ionic concentration impact the intercalation process? A comprehensive microsecond time-scale molecular dynamics study in an explicit aqueous solvent has been performed to address the above-raising questions. In this study, DOX interacts with different dsDNA sequences of various lengths (hexamer or tetradecamer). The molecular mechanics Poisson-Boltzmann or generalized-Born surface area (MM-PB(GB)SA) method is adapted to quantify and partition the binding free energy (BFE) into its thermodynamic components, for a variety of different solution conditions and different DNA sequences. Our results show that the compulsory DNA conformational changes to form the intercalation cavity, the loss of translational and rotational mobility upon complex formation, and the overall electrostatic interactions are all unfavorable for the DOX-DNA complexation process. However, they are counteracted by the favorable contributions from the attractive van der Waals interaction, the non-polar solvation interaction, the vibrational entropic contribution, and the polyelectrolyte free energy at lower ionic strength. The van der Waals interaction provides the largest contribution to the BFE at each stage of binding. The sequence selectivity depends mainly on the base pairs located downstream from the DOX intercalation site, with a preference for (AT)2 or (TA)2 driven by the favorable electrostatic and/or van der Waals interactions. Invoking the quartet sequence model proved to be most successful to predict the sequence selectivity. Our findings indicate that the aqueous bathing solution (i.e. water and ions) opposes the formation of the DOX-DNA complex at every binding stage, thus implying that this process preferably occurs at low ionic strength and is crucially dependent on solvent effects.Introduction -- Theory and methodology -- Molecular mechanism and binding free energy doxorubicin Intercalation in DNA -- Thermodynamic dissection and sequence selectivity of doxorubicin-DNA interaction -- Final remarks and future work -- Appendix. Supporting tables and figure

Sobiva omaduste profiiliga ühendite tuvastamine keemiliste struktuuride andmekogudest

Keemiliste ühendite digitaalsete andmebaaside kasutuselevõtuga kaasneb vajadus leida neist arvutuslikke vahendeid kasutades sobivate omadustega molekule. Probleem on eriti huvipakkuv ravimitööstuses, kus aja- ja ressursimahukate katsete asendamine arvutustega, võimaldab märkimisväärset säästu. Kuigi tänapäevaste arvutusmeetodite piiratud võimsuse tõttu ei ole lähemas tulevikus võimalik kogu ravimidisaini protsessi algusest lõpuni arvutitesse ümber kolida, on lugu teine, kui vaadelda suuri andmekogusid. Arvutusmeetod, mis töötab teadaoleva statistilise vea piires, visates välja mõne sobiva ühendi ja lugedes mõni ekslikult aktiivseks, tihendab lõppkokkuvõttes andmekomplekti tuntaval määral huvitavate ühendite suhtes. Seetõttu on ravimiarenduse lihtsamate ja vähenõudlikkumade etappide puhul, nagu juhtühendite või ravimikandidaatide leidmine, edukalt võimalik rakendada arvutuslikke vahendeid. Selline tegevus on tuntud virtuaalsõelumisena ning käesolevasse töösse on sellest avarast ja kiiresti arenevast valdkonnast valitud mõningad suunad, ning uuritud nende võimekust ja tulemuslikkust erinevate projektide raames. Töö tulemusena on valminud arvutusmudelid teatud tüüpi ühendite HIV proteaasi vastase aktiivsuse ja tsütotoksilisuse hindamiseks; koostatud uus sõelumismeetod; leitud potentsiaalsed ligandid HIV proteaasile ja pöördtranskriptaasile; ning kokku pandud farmakokineetiliste filtritega eeltöödeldud andmekomplekt – mugav lähtepositsioon edasisteks töödeks.With the implementation of digital chemical compound libraries, creates the need for finding compounds from them that fit the desired profile. The problem is of particular interest in drug design, where replacing the resource-intensive experiments with computational methods, would result in significant savings in time and cost. Although due to the limitations of current computational methods, it is not possible in foreseeable future to transfer all of the drug development process into computers, it is a different story with large molecular databases. An in silico method, working within a known error margin, is still capable of significantly concentrating the data set in terms of attractive compounds. That allows the use of computational methods in less stringent steps of drug development, such as finding lead compounds or drug candidates. This approach is known as virtual screening, and today it is a vast and prospective research area comprising of several paradigms and numerous individual methods. The present thesis takes a closer look on some of them, and evaluates their performance in the course of several projects. The results of the thesis include computational models to estimate the HIV protease inhibition activity and cytotoxicity of certain type of compounds; a few prospective ligands for HIV protease and reverse transcriptase; pre-filtered dataset of compounds – convenient starting point for subsequent projects; and finally a new virtual screening method was developed

Regioselective Synthesis of Biologically Active Pyrazolone Nucleosides and their Benzoyl Analogues

Increasing incidence of anticancer and antimicrobial resistance are the most common concerns in the medical field. Cancer is a serious disease that can affect almost every tissue lineage in the human body and poses great challenges to medicinal science. In addition, many antibiotics have a tendency to becoming resistant and are prone to severe adverse effects after long term use. Hence, there is an urgent need to discover and develop novel antitumor drug molecules which could effectively inhibit proliferative pathways with fewer side effects. Also, increasing demand to synthesize novel antimicrobial agents that are active against resistant strains. This research aimed to design, synthesis, physical studies and biochemical evaluated of some novel pyrazolones and their corresponding ribonucleoside, deoxyribonucleoside and benzoyl analogues for their in vitro antimicrobial and anticancer activities. Antimicrobial properties of the title compounds were investigated against Gram positive and Gram negative bacterial as well as fungal strains. Anticancer activity was performed against HL60 cell lines. Antimicrobial activity results revealed that the synthesized azo compound 113c, and the synthesized nucleosides compounds 116a and 118c were found to be the most effective agents with better MIC values, compared to some existing antimicrobial drugs, such as Ceftriaxone and Amphotericin B. On the other hand, the results of anticancer study indicated that the synthesized nucleosides 117a, 122a,b and 123 were found to be most potent anticancer agent against the cancerous HL60 cell line while the synthesized nucleosides 117e,f, 122a and the benzoylated compounds 124c,d,f, and 124g showed good affect against the A-549 cell line. Also, pyrazolones derivatives are more sensitive against the lung cancer. Binding affinity and selectivity of the synthesized compounds towards ct-DNA were studied at different conditions of pH and solvents; the results showed that compound 118c interact and stabilize the ct-DNA which can be anti-cancer agent. Therefore, these compounds, open new avenues for the development of antibacterial and anti-cancer therapeutic agents for the treatment of infectious and cancer diseases. Also, these results give an insight into the structure-activity relationships, which are tremendously important for the design of further new antimicrobial and anticancer agents

Thirty-second Annual Symposium of Trinity College Undergraduate Research

2019 annual volume of abstracts for science research projects conducted by students at Trinity College