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

Diverse computational tools towards the understanding of HIV targets and design of potential drug candidates.

Ph. D. University of KwaZulu-Natal, Durban 2014.HIV/AIDS still remains to be a challenging epidemic infecting millions of individuals worldwide. The morbidity and mortality rates of HIV-infected patients has been well documented over the years. Despite on-going HIV/AIDS research and access to antiretroviral therapy, to date still no cure exists for this deliberating disease. In recent years, computational approaches have emerged as close counterparts to experiments in modern drug discovery process and in understanding complex biological phenomena. An array of in-silico computational techniques were implemented ranging from molecular dynamic (MD) simulations, de-novo design, hybrid structure-based and pharmacophore-based virtual screening, quantitative structure-activity relationship (QSAR), homology modeling, principle component analysis (PCA), residue interaction network analysis (RIN), substrate envelope analysis (SEA), to molecular mechanics and quantum mechanics. The first report (Chapter 4), demonstrated a unique strategy for developing dual acting inhibitors against HIV-1 protease (PR) and reverse transcriptase (RT). The designed targets exhibited binding affinities and dual inhibiting activity comparable to, and in some cases better than, known active reference drugs. The second study (Chapter 5), reported the activity of flexible hydroquinone-based compounds as non-nucleoside reverse transcriptase inhibitors (NNRTIs), as proposed by Bruccoleri, where no experimental or computational work supported his proposal. Results concluded that the novel flexible hydroquinone-based compounds showed improved binding affinity as compared to FDA-approved prototype drugs and more specifically potent potential mutant-resistant NNRT inhibitor activity. The third report (Chapter 6), explored the activity of novel CCR5 antagonists as potential HIV- 1 entry inhibitors. Ten scaffolds were identified as novel CCR5 antagonists or potential HIV-1 entry inhibitors. Furthermore, from the generated atom-based 3D-QSAR model, all of the parameters showed certain reliability and feasible predictability to help us design new and high selectivity CCR5 inhibitors. The fourth study (Chapter 7), explored the atomistic basis of why the M184I single mutation renders complete resistance of HIV-1 RT to lamivudine. Multiple molecular dynamics simulations, binding free energy calculations, principle component analysis (PCA) and residue interaction network (RIN) analyses adequately clarified the effect of the M184I mutation on drug resistance to lamvudine. Results presented in this study verified that M184I mutation decreased drug binding affinity, distorted ligand optimum orientation in RT active site and affected the overall protein conformational landscape. The results also provided some potential clues for further design of novel inhibitors that are less susceptible to drug resistance. In the fifth study (Chapter 8), we identified potential HIV-Nef inhibitors by exploiting the structural features of B9 using an integrated computational tools framework. The top identified hit compounds demonstrated comparatively better binding affinities and relatable binding modes compared to the prototype antagonist, B9. Top identified hits were proposed as new potential novel leads targeting HIV-Nef with a detailed analysis of their respective binding modes. The sixth report (Chapter 9), aimed to reveal the dimer packing and unpacking phenomena of HIV-Nef in its apo and inhibitor bound conformations using molecular dynamic simulations. Results verified a more conformational flexible nature of HIV-Nef dimer in the absence of an inhibitor.as compared to B9 bound conformation of HIV-Nef, which was found to be more conformationally rigid with a lesser inter-dimeric association. We believe that the results obtained from these several studies could be of great benefit in the development of more effective therapeutic interventions for the treatment and cure of HIV/AIDS

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

Peptide Inhibitors Targeting the \u3cem\u3eNeisseria gonorrhoeae\u3c/em\u3e Pivotal Anaerobic Respiration Factor AniA

Neisseria gonorrhoeae causes the sexually transmitted infection gonorrhea, which is highly prevalent worldwide and has a major impact on reproductive and neonatal health. The superbug status of N. gonorrhoeae necessitates the development of drugs with different mechanisms of action. Here, we focused on targeting the nitrite reductase AniA, which is a pivotal component of N. gonorrhoeae anaerobic respiration and biofilm formation. Our studies showed that gonococci expressing AniA containing the altered catalytic residues D137A and H280A failed to grow under anaerobic conditions, demonstrating that the nitrite reductase function is essential. To facilitate the pharmacological targeting of AniA, new crystal structures of AniA were refined to 1.90-Å and 2.35-Å resolutions, and a phage display approach with libraries expressing randomized linear dodecameric peptides or heptameric peptides flanked by a pair of cysteine residues was utilized. Biopanning experiments led to the identification of 29 unique peptides, with 1 of them, C7-3, being identified multiple times. Evaluation of their ability to interact with AniA using enzyme-linked immunosorbent assay and computational docking studies revealed that C7-3 was the most promising inhibitor, binding near the type 2 copper site of the enzyme, which is responsible for interaction with nitrite. Subsequent enzymatic assays and biolayer interferometry with a synthetic C7-3 and its derivatives, C7-3m1 and C7-3m2, demonstrated potent inhibition of AniA. Finally, the MIC50 value of C7-3 and C7-3m2 against anaerobically grown N. gonorrhoeae was 0.6 mM. We present the first peptide inhibitors of AniA, an enzyme that should be further exploited for antigonococcal drug development

Mechanistic Elucidation of Protease–Substrate and Protein–Protein Interactions for Targeting Viral Infections

Viral infections represent an old threat to global health, with multiple epidemics and pandemics in the history of mankind. Despite several advances in the development of antiviral substances and vaccines, many viral species are still not targeted. Additionally, new viral species emerge, posing a menace without precedent to humans and animals and causing fatalities, disabilities, environmental harm, and economic losses. In this thesis, we present rational modeling approaches for targeting specific protease-substrate and protein-protein interactions pivotal for the viral replication cycle. Over the course of this work, antiviral research is supported beginning with the development of small molecular antiviral substances, going through the modeling of a potential immunogenic epitope for vaccine development, towards the establishment of descriptors for susceptibility of animals to a viral infection. Notably, all the research was done under scarce data availability, highlighting the predictive power of computational methods and complementarity between in-silico and in-vitro or in-vivo methods

Biochemical and structural characterization of mycobacterial aspartyl-tRNA synthetase AspS, a promising TB drug target.

The human pathogen Mycobacterium tuberculosis is the causative agent of pulmonary tuberculosis (TB), a disease with high worldwide mortality rates. Current treatment programs are under significant threat from multi-drug and extensively-drug resistant strains of M. tuberculosis, and it is essential to identify new inhibitors and their targets. We generated spontaneous resistant mutants in Mycobacterium bovis BCG in the presence of 10× the minimum inhibitory concentration (MIC) of compound 1, a previously identified potent inhibitor of mycobacterial growth in culture. Whole genome sequencing of two resistant mutants revealed in one case a single nucleotide polymorphism in the gene aspS at 535GAC>535AAC (D179N), while in the second mutant a single nucleotide polymorphism was identified upstream of the aspS promoter region. We probed whole cell target engagement by overexpressing either M. bovis BCG aspS or Mycobacterium smegmatis aspS, which resulted in a ten-fold and greater than ten-fold increase, respectively, of the MIC against compound 1. To analyse the impact of inhibitor 1 on M. tuberculosis AspS (Mt-AspS) activity we over-expressed, purified and characterised the kinetics of this enzyme using a robust tRNA-independent assay adapted to a high-throughput screening format. Finally, to aid hit-to-lead optimization, the crystal structure of apo M. smegmatis AspS was determined to a resolution of 2.4 Å

Virtual Screening for HIV Protease Inhibitors: A Comparison of AutoDock 4 and Vina

BACKGROUND: The AutoDock family of software has been widely used in protein-ligand docking research. This study compares AutoDock 4 and AutoDock Vina in the context of virtual screening by using these programs to select compounds active against HIV protease. METHODOLOGY/PRINCIPAL FINDINGS: Both programs were used to rank the members of two chemical libraries, each containing experimentally verified binders to HIV protease. In the case of the NCI Diversity Set II, both AutoDock 4 and Vina were able to select active compounds significantly better than random (AUC = 0.69 and 0.68, respectively; p<0.001). The binding energy predictions were highly correlated in this case, with r = 0.63 and iota = 0.82. For a set of larger, more flexible compounds from the Directory of Universal Decoys, the binding energy predictions were not correlated, and only Vina was able to rank compounds significantly better than random. CONCLUSIONS/SIGNIFICANCE: In ranking smaller molecules with few rotatable bonds, AutoDock 4 and Vina were equally capable, though both exhibited a size-related bias in scoring. However, as Vina executes more quickly and is able to more accurately rank larger molecules, researchers should look to it first when undertaking a virtual screen

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

Molecular modeling studies on HIV-1 Reverse Transcriptase (RT) and Heat shock protein (Hsp) 90 as a potential anti-HIV-1 target.

Masters Degree. University of KwaZulu-Natal, Durban.Human immunodeficiency virus (HIV) infection is the leading cause of death globally. This dissertation addresses two HIV-1 target proteins namely, HIV-1 Reverse Transcriptase (RT) and Heat shock protein (Hsp) 90. More specifically for HIV-1 RT, a case study for the identification of potential inhibitors as anti-HIV agents was carried out. A more refined virtual screening (VS) approach was implemented, which was an improvement on work previously published by our group- “target-bound pharmacophore modeling approach”. This study generated a pharmacophore library based only on highly contributing amino acid residues (HCAAR), instead of arbitrary pharmacophores, most commonly used in the conventional approaches in literature. HCAAR were distinguished based on free binding energy (FBE) contributions, obtained using calculation from molecular dynamics (MD) simulations. Previous approaches have relied on the docking score (DS) to generate energy-based pharmacophore models. However, DS are reportedly unreliable. Thus we present a model for a per-residue energy decomposition (PRED), constructed from MD simulation ensembles generating a more trustworthy pharmacophore model which can be applied in drug discovery workflow. This approach was employed in screening for potential HIV-1 RT inhibitors using the pharmacophoric features of the compound GSK952. The complex was subjected to docking and thereafter MD simulations confirmed the stability of the system. Experimentally determined inhibitors with known HIV-RT inhibitory activity were used to validate the proposed protocol. Two potential hits ZINC46849657 and ZINC54359621 showed a significant potential with regards to FBE. Reported results obtained from this work confirm that this new approach is favourable to the future of drug design process. Hsp90 was recently discovered to play a vital role in HIV-1 replication. Thus has emerged, as a promising target for anti-HIV-1 drugs. The molecular mechanism of Hsp90 is poorly understood, thus the second study was aimed to address this issue and provide a clear insight to the inhibition mechanism of Hsp90. Reasonable continuous MD simulations were employed for both unbound and bound Hsp90 conformations, to understand the dimerization and inhibition mechanisms. Results demonstrated that coumermycin A1 (C-A1), a newly discovered Hsp90 inhibitor, binds at the CTD dimer of Hsp90 and lead to a significant separation between orthogonally opposed residues, such as Arg591.B, Lys594.A, Ser663.A, Thr653.B, Ala665.A, Thr649.B, Leu646.B and Asn669A. A Large difference in magnitudes was observed in the radius of gyration (Rg), per-residue fluctuation, root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) confirming a completely more flexible state for the unbound conformation associated with dimerization. Whereas, a less globally correlated motion in the case of the bound conformer of Hsp90 approved a reduction of the dimeric process. This undoubtedly underlines the inhibition process due to ligand binding. The detailed dynamic analyses of Hsp90 presented herein are believed to give a greater insight and understanding to the function and mechanisms of inhibition of Hsp90. The report on the inhibitor-binding mode would also be of great assistance in the design of prospective inhibitors against Hsp90 as potential HIV target