Computational methods are a convenient resource to solve drawbacks of drug research such as high cost, time-consumption, and high risk of failure. In order to get an optimum search of new drugs we need to design a rational approach to analyze the molecular forces that govern the interactions between the drugs and their target molecules. The objective of this project is to get an understanding of the interactions between drugs and proteins at the molecular level. The interaction energy, when protein and drugs react, has two components: non-covalent and covalent. The former accounts for the ionic interactions, the later accounts for electron transfer between the reactants. We study each energy component using the most popular analysis tools in computational chemistry such as docking scoring, molecular dynamics fluctuations, electron density change, molecular electrostatic potential (MEP), density of states projections, and the transmission function. We propose the probability of transfer of electrons (transmission function) between reactants in protein-drug complexes as an alternative tool for molecular recognition and as a direct correlator to the binding affinity. The quadratic correlation that exists between the electron transfer rate and the electronic coupling strength of the reactants allow a clear distinguishability between ligands. Thus, in order to analyze the binding affinity between the reactants, a calculation of the electronic coupling between them is more suitable than an overall energetic analysis such as free reaction energy.

Though the Aerospace industry is moving towards small satellites and smaller sensor technologies, sensors used for close-proximity operations are generally cost (and often size and power) prohibitive for University-class satellites. Given the need for low-cost, low-mass solutions for close-proximity relative navigation sensors, this research analyzed the expected errors due to near-field effects using a coarse sun sensor as part of a 6-degree-of-freedom (6-dof) solution. To characterize these near-field effects, a test bed (Characterization Test Apparatus or CTA) was proposed, its design presented, and the design stage uncertainty analysis of the CTA performed. A candidate coarse sun sensor (NorthStarTM) was chosen for testing, and a mathematical model of the sensor’s functionality was derived. Using a Gaussian Least Squares Differential Correction (GLSDC) algorithm, the model parameters were estimated and a comparison between simulated NorthStarTM measurements and model estimates was performed. Results indicate the CTA is capable of resolving the near-field errors. Additionally, this research found no apparent show stoppers for using coarse sun sensors for 6-dof solutions.

Glycogen synthase kinase-3 (GSK-3) is a serine/threonine protein kinase which plays a key role in several signaling pathways and its homologues have been identified in most eukaryotes. Since GSK3£]is an essential protein kinase that regulates numerous functions within the cell, an effort to survey possible GSK3£]- interacting proteins from a human testis cDNA library using the yeast two-hybrid system is made. Two interesting candidates are chosen to characterize their functions in this study. One is a centrosomal protein, hNinein, and the other is a novel inhibitor of GSK3£], designated as GSKIP (GSK3£] interaction protein). In the first part of the present thesis we describe the identification of four diverse CCII-termini of human hNinein isoforms, including a novel isoform 6, by differential expression in a tissue-specific manner. In a kinase assay, the CCII region of hNinein isoforms provides a differential phosphorylation site by GSK3£]. In addition, either N-terminal or CCIIZ domain disruption may cause hNinein conformational change which recruits £^-tubulin to centrosomal or non-centrosomal hNinein-containing sites. Further, depletion of all hNinein isoforms caused a significant decrease in the £^-tubulin signal in the centrosome. In domain swapping, it clearly shows that the CCIIX-CCIIY region provides docking sites for £^-tubulin. Moreover, nucleation of microtubules from the centrosome is significantly affected by the overexpression of either the full-length hNinein or CCIIX-CCIIY region. Taken together, these results show that the centrosomal targeting signals of hNinein have a role not only in regulating hNinein conformation, resulting in localization change, but also provide docking sites to recruit £^-tubulin at centrosomal and non-centrosomal sites. In the second part of the thesis we describe another candidate, GSK3£]interaction protein (GSKIP), to characterize its functions in neuron differentiation. We use human neuroblastoma SH-SY5Y cells as a model of neuronal cell differentiation. When overexpression of GSKIP prevents neurite outgrowth from RA-mediated differentiation, this result is similar to the presence of LiCl or SB415286, an inhibitor of GSK3£]. Further, GSKIP regulates the activity of GSK3£] through protein-protein interactions rather than post-modulation and GSKIP may affect GSK3£] on neurite outgrowth via inhibiting the specific phosphorylation site of tau. In addition to inhibition of neurite outgrowth, GSKIP overexpressed in SH-SY5Y cells also promotes cell cycle progression by analyzing cell proliferation with cell growth and MTT assay. Furthermore, GSKIP raises the level of £]-catenin and cyclin D1 through inhibition of GSK3£] activity in RA-mediated differentiation SH-SY5Y cells. Taken together, the data suggest that GSKIP, a dual functional molecule, is able to inhibit neurite outgrowth and promote cell proliferation via negative regulation of GSK3£] activity in RA-mediated differentiation of SH-SY5Y cells.

An in silico design algorithm has been developed to design binding ligands for protein targets of known three-dimensional structure. In this method, the binding energy of a candidate ligand is used to ascribe it a probability of binding. A sample of a virtual library of candidate ligands is then used to ascribe implicit weights to all the ligands in the library. These weights are used to obtain virtual sub-libraries which collectively carry a greater probability to bind to the target. This algorithm is presented along with validation studies on the different algorithmic components, demonstrating how optimization of the design method can be best achieved.

Computational structural biology Even with rapid advances in structure determination methods, there is a long gap to be bridged between the number of proteins that have been sequenced and the number whose three-dimensional structures have been experimentally elucidated. Experimentally protein structures are determined by X-ray crystallography or by nuclear magnetic resonance spectroscopy (NMR). X-ray crystal structures give a time averaged picture but little information on conformational dynamics. Though NMR gives dynamical information, the technique cannot be applied to systems whose molecular weight is large. Only small proteins fall within the ken of NMR experiments. In most cases the three dimensional structure of the protein alone cannot give a complete picture of its mechanism. It is also essential to know the interactions of proteins with other proteins, with their ligands and substrates in order to have a better understanding of their functioning. Computer modeling and simulations are now indispensable supplements to experimental structural biology. The last word in protein structure prediction method is far from being said but the ever-improving homology and ab-initio modeling methods give rise to optimism that sometime in the near future these methods will become almost as reliable as experimental techniques. Ligand docking onto protein molecules is as challenging a problem as protein structure predicting itself. Computer modeling methods to dock ligands have to search a wide region of conformational space besides taking into consideration issues of charge and shape complementarities.

<p>In this dissertation a novel approach to protein-ligand docking is presented. First an existing method to predict putative active sites is employed. These predictions are then used to cut down the search space of an algorithm that uses the fast Fourier transform to calculate the geometrical and electrostatic complementarity between a protein and a small organic ligand. A simplified hydrophobicity score is also calculated for each active site. The docking method could be applied either to dock ligands in a known active site or to rank several putative active sites according to their biological feasibility. The method was evaluated on a set of 310 protein-ligand complexes. The results show that with respect to docking the method with its initial parameter settings is too coarse grained. The results also show that with respect to ranking of putative active sites the method works quite well.</p>

This study compares the biomechanics of early cyclic valgus loading of the ulnar collateral ligament (UCL) of the elbow repaired by either the Jobe technique or the docking technique. Better understanding of the biomechanical properties of each reconstruction may help surgeons choose the optimal surgical technique, particularly in planning earlier rehabilitation programs. Sixteen fresh frozen cadaver limbs (eight pairs) were randomized to either the Jobe cohort or the docking cohort. First intact UCLs were tested, followed by the repaired constructions. A Bionix MTS apparatus applied a constant valgus load to the elbows at 70o flexion, and valgus displacement was measured and then used to calculate valgus angle displacement. The docking group had significantly less valgus angle displacement than the Jobe group at cycles 100 and 1,000 (p = 0.0189 and 0.0076, respectively). Four of the eight specimens in the Jobe group failed at the tendon-suture interface before reaching 1,000 cycles, at cycles 7, 24, 250, and 362. None of the docking specimens failed before reaching 1,000 cycles. In this cadaveric study, the docking technique resulted in less angulation of the elbow in response to cyclic valgus loading as compared to the Jobe technique. The better response to valgus loading of the docking reconstruction may translate into a better response to early rehabilitation. Further study is needed to determine if this difference translates into improved clinical outcomes.

The scope of this work focuses on computationally modeling compounds with protein structures. While the impetus of drug discovery is the innovation of new therapeutic molecules, it also involves distinguishing molecules that would not be an effective drug. This can be achieved by inventing new tools or by refining old tools. Virtual screening (VS, also called docking), the computational modeling of a molecule in a receptor structure, is a staple in predicting a molecule's affinity for an intended target. In our Virtual Target Screening system (also called inverse-docking), VS is used to find high-affinity targets, which can potentially explain absorption, distribution, metabolism, and excretion (ADME) of a molecule of interest in the human body. The next project, low-mode docking (LD), attempts to improve VS by incorporating protein flexibility into traditional docking where a static receptor structure has potential to produce poor results due to incorrectly predicted ligand poses. Finally, VS, performed mostly on small molecules, is scaled up to cyclic peptides by employing Monte Carlo simulations and molecular dynamics to mimic the steps of small molecule VS. The first project discussed is Virtual Target Screening (also called inverse-docking) where a small molecule is virtually screened against a library of protein structures. Predicting receptors to which a synthesized compound may bind would give insights to drug repurposing, metabolism, toxicity, and lead optimization. Our protocol calibrates each protein entry with a diverse set of small molecule structures, the NCI Diversity Set I. Our test set, 20 kinase inhibitors, was predicted to have a high percentage of kinase "hits" among approximately 1500 protein structures. Further, approved drugs within the test set generally had better rates of kinase hits. Next, normal mode analysis (NMA), which can computationally describe the fundamental motions of a receptor structure, is utilized to approach the rigid body bias problem in traditional docking techniques. Traditional docking involves the selection of a static receptor structure for VS; however, protein structures are dynamic. Simulation of the induced fit effect in protein-ligand binding events is modeled by full articulation of the approximated large-scale low-frequency normal modes of vibration, or "low-modes," coupled with the docking of a ligand structure. Low-mode dockings of 40 cyclin dependent 2 (CDK2) inhibitors into 54 low-modes of CDK2 yielded minimum root-mean-square deviation (RMSD) values of 1.82 – 1.20 Å when compared to known coordinate data. The choice of pose is currently limited to docking score, however, with ligand pose RMSD values of 3.87 – 2.07 Å. When compared to corresponding traditional dockings with RMSD values of 5.89 – 2.33 Å, low-mode docking was more accurate. The last discussion involves the rational docking of a cyclic peptide to the murine double minute 2 (MDM2) oncoprotein. The affinity for a cyclic peptide (synthesized by Priyesh Jain, McLaughin Lab, University of South Florida), PJ-8-73, in MDM2 was found to be within an order of magnitude of a cyclic peptide from the Robinson Lab at the University of Zurich in Switzerland. Both are Β-hairpin cyclic peptides with IC50 values of 650 nm and 140 nm, respectively. Using the co-crystalized structure of the Robinson peptide (PDB 2AXI), we modeled the McLaughlin peptide based on an important interaction of the 6-chloro-tryptophan residue of the Robinson peptide occupying the same pocket in MDM2 as the tryptophan residue by the native p53 transactivation helical domain. By preserving this interaction in initial cyclic peptide poses, the resulting pose of PJ-8-73 structure in MDM2 possessed comparable active site residue contacts and surface area. These protocols will aid medical research by using computer technology to reduce cost and time. VTS utilizes a unique structural and statistical calibration to virtually assay thousands of protein structures to predict high affinity binding. Determining unintended protein targets aids in creating more effective drugs. In low-mode docking, the accuracy of virtual screening was increased by including the fundamental motions of proteins. This newfound accuracy can decrease false negative results common in virtual screening. Lastly, docking techniques, usually for small molecules, were applied to larger peptide molecules. These modifications allow for the prediction of peptide therapeutics in protein-protein interaction modulation, a growing interest in medicine. Impactful in their own ways, these procedures contribute to the discovery of drugs, whether they are small molecules or cyclic peptides.

This dissertation research was aimed at investigating an interesting class of 1,2-dialkynylimidazoles as: 1. irreversible p38 MAP kinase α-isoform (p38α) inhibitors; 2. p38α docking site probes; 3. anti-cancer agents. Based on the mild, thermal rearrangement of 1,2-dialkynylimidazoles to reactive carbene or diradical intermediates, a series of 1,2-dialkynylimidazoles was designed as potential irreversible p38α inhibitors. The synthesis of these dialkynylimidazoles and their kinase inhibition activity were reported. Interestingly, one of the 1-ethynyl-substituted dialkynylimidazoles is a potent (IC50 = 200 nM) and selective inhibitor of p38α. Additionally, this compound covalently modifies p38α as determined by ESI-MS after 12 h incubation at 37 °C. The unique kinase inhibition, covalent kinase adduct formation, and minimal CYP450 2D6 inhibition by this compound demonstrate that dialkynylimidazoles are a new, promising class of p38α inhibitors. Blocking docking interactions between kinase network partners is a promising alternative approach for selectively inhibiting kinases. The second project involves the identification of a new class of small molecules, covalent p38α MAP kinase docking site probes. We proposed that the mechanism may involve the addition of a thiol to the N-ethynyl group. Moreover, we demonstrated that such probes can be used fluorescently to label p38α both in vitro and in cells via azide-alkyne “Click” chemistry. This serves as the basis of an assay that can be used to identify inhibitors that specifically target the substrate docking site of p38α. The last project was focused on evaluating a new class of 1,2-dialkynylimidazoles as anti-cancer agents. One 1,2-dialkynylimidazole analog was found to be cytotoxic against a range of human cancer lines and to induce apoptosis in the human non-small cell lung cancer cell line A549. In order to elucidate the relationship between the structural basis and role of the thermal generation of diradical or carbene intermediates, a series of dialkynylimidazoles and related N-alkynylimidazoles was prepared and their cytotoxicity was determined against A549 cell line. Although the experimentally determined activation energy is in excellent agreement with that predicated from the DFT calculation, there is no correlation between the rate of Bergman cyclization and cytotoxicity to A549 cells. An alternative mechanism was proposed involving the unexpected selective thiol addition to the N-ethynyl group of certain 1,2-dialkynylimidazoles. / text

Στα πλαίσια της συγκεκριμένης μεταπτυχιακής εργασίας μελετήθηκαν αλγόριθμοι και εργαλεία σχεδίασης φαρμάκων με τη βοήθεια Η/Υ που υπάρχουν στη διεθνή βιβλιογραφία. Η μελέτη εστιάστηκε σε αλγορίθμους ανάκτησης πιθανών φαρμακοφόρων μορίων από Βάσεις Βιολογικών Δεδομένων (search algorithms for virtual ligand screening), με χρήση της μεθόδου μοριακής αναγνώρισης (docking method). Η μέθοδος αυτή προσπαθεί να εντοπίσει μικρά μόρια-προσδέτες τα οποία ταιριάζουν, όσο το δυνατόν καλύτερα, στην κοιλότητα πρόσδεσης των μακρομορίων-στόχων που μας ενδιαφέρουν. Το ταίριασμα στηρίζεται στην ικανοποίηση: - γεωμετρικών κριτηρίων, τα οποία ελέγχουν την συμπληρωματικότητα στις δομές (σχήματα) των μορίων που επιδιώκουμε να ταιριάσουμε, και - ενεργειακών κριτηρίων τα οποία εξασφαλίζουν ότι αναπτύσσονται οι βέλτιστες αλληλεπιδράσεις μεταξύ των εμπλεκόμενων μορίων. Στόχος της διπλωματικής εργασίας ήταν η σχεδίαση ενιαίου πλαισίου αξιολόγησης των σχετικών εργαλείων και αλγορίθμων σχεδιασμού Φαρμάκων, ώστε να αποτελέσει βάση για περαιτέρω έρευνα, εντοπίζοντας ανοικτά προβλήματα ή/και προτείνοντας πιθανές βελτιώσεις. / In this dissertation algorithms and tools for computer-aided drug design that are available in the international bibliography were studied. The study focussed on virtual screening search algorithms and tools using the docking methodology, which locates small molecules (ligands) with optimal fit in the binding cavity of the target macromolecules of interest. Fit is based in the fulfilment of: - geometric criteria, which check for structural complementarity of the molecules involved and - energetic criteria, which check for optimal interactions between the molecules. The goal of this study was to develop an evaluation context for tools and algorithms used for computer-aided drug design in order to be used as the basis for further research and help us proposing possible improvements or addressing open problems.