<p>Malaria is a widespread disease caused by parasites of the genus <i>Plasmodium</i>. Each year 500 million clinical cases are reported resulting in over one million casualties. The most lethal species, <i>P. falciparum</i>, accounts for ~90% of the fatal cases and has developed resistance to chloroquine. The resistant strains are a major problem and calls for novel drugs.</p><p>In this thesis, the process of computational inhibitor design is illustrated through the development of <i>P. falciparum</i> aspartic protease inhibitors. These proteases, called plasmepsins, are part of the hemoglobin degradation chain. The hemoglobin is degraded during the intraerythrocytic cycle and serves as the major food source. By inhibiting plasmepsins the parasites can be killed by starvation.</p><p>Novel inhibitors with very high affinity were found by using a combination of computational and synthetic chemistry. These inhibitors were selective and did not display any activity on human cathepsin D. The linear interaction energy (LIE) method was utilized in combination with molecular dynamics (MD) simulations to estimate free energies of binding. The MD simulations were also used to characterize the enzyme–inhibitor interactions and explain the binding on a molecular level.</p><p>The influence of the partial charge model on binding free energy calculations with the LIE method was assessed. Two semiempirical and six <i>ab initio</i> quantum chemical charge derivation schemes were evaluated. It was found that the fast semiempirical charge models are equally useful in free energy calculations with the LIE method as the rigorous <i>ab initio</i> charge models.</p>

Background: Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results: We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion: While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structurebased P-site prediction method has been made available at http://phos3d.mpimp-golm.mpg.de.

Malaria is a widespread disease caused by parasites of the genus Plasmodium. Each year 500 million clinical cases are reported resulting in over one million casualties. The most lethal species, P. falciparum, accounts for ~90% of the fatal cases and has developed resistance to chloroquine. The resistant strains are a major problem and calls for novel drugs. In this thesis, the process of computational inhibitor design is illustrated through the development of P. falciparum aspartic protease inhibitors. These proteases, called plasmepsins, are part of the hemoglobin degradation chain. The hemoglobin is degraded during the intraerythrocytic cycle and serves as the major food source. By inhibiting plasmepsins the parasites can be killed by starvation. Novel inhibitors with very high affinity were found by using a combination of computational and synthetic chemistry. These inhibitors were selective and did not display any activity on human cathepsin D. The linear interaction energy (LIE) method was utilized in combination with molecular dynamics (MD) simulations to estimate free energies of binding. The MD simulations were also used to characterize the enzyme–inhibitor interactions and explain the binding on a molecular level. The influence of the partial charge model on binding free energy calculations with the LIE method was assessed. Two semiempirical and six ab initio quantum chemical charge derivation schemes were evaluated. It was found that the fast semiempirical charge models are equally useful in free energy calculations with the LIE method as the rigorous ab initio charge models.

A drug discovery project typically starts with a pharmacological hypothesis: that the modulation of a specific molecular biological mechanism would be beneficial in the treatment of the targeted disease. In a small-molecule project, the next step is to identify hits, i.e. molecules that can effect this modulation. These hits are subsequently expanded into hit series, which are optimised with respect to pharmacodynamic and pharmacokinetic properties, through medicinal chemistry. Finally, a drug candidate is clinically developed into a new drug. This thesis concerns the use of structure-based virtual screening in the hit identification phase of drug discovery. Structure-based virtual screening involves using the known 3D structure of a target protein to predict binders, through the process of docking and scoring. Docking is the prediction of potential binding poses, and scoring is the prediction of the free energy of binding from those poses. Two new methodologies, based on post-processing of scoring results, were developed and evaluated using model systems. Both methods significantly increased the enrichment of true positives. Furthermore, correlation was observed between scores and simple molecular properties, and identified as a source of false positives in structure-based virtual screening. Two target proteins, Mycobacterium tuberculosis ribose-5-phosphate isomerase, a potential drug target in tuberculosis, and Plasmodium falciparum spermidine synthase, a potential drug target in malaria, were subjected to docking and virtual screening. Docking of substrates and products of ribose-5-phosphate isomerase led to hypotheses on the role of individual residues in the active site. Additionally, virtual screening was used to predict 48 potential inhibitors, but none was confirmed as an inhibitor or binder to the target enzyme. For spermidine synthase, structure-based virtual screening was used to predict 32 potential active-site binders. Seven of these were confirmed to bind in the active site.

The main topic of this thesis is the development of computational search methods that are useful in drug design applications. The emphasis is on exhaustiveness of the search method such that it can guarantee a certain level of geometric accuracy. In particular, the following two problems are addressed: (i) Prediction of binding mode of a drug molecule to a receptor and (ii) prediction of crystal structures of drug molecules. Predicting the binding mode(s) of a drug molecule to a target receptor is pivotal in structure-based rational drug design. In contrast to most approaches to solve this problem, the idea in this work is to analyze the search problem from a computational perspective. By building on top of an existing docking tool, new methods are proposed and relevant computational results are proven. These methods and results are applicable for other place-and-join frameworks as well. A fast approximation scheme for the docking of rigid fragments is described that guarantees certain geometric approximation factors. It is also demonstrated that this can be translated into an energy approximation for simple scoring functions. A polynomial time algorithm is developed for the matching phase of the docked rigid fragments. It is demonstrated that the generic matching problem is NP-hard. At the same time the optimality of the proposed algorithm is proven under certain scoring function conditions. The matching results are also applicable for some of the fragment-based de novo design methods. On the practical side, the proposed method is tested on 829 complexes from the PDB. The results show that the closest predicted pose to the native structure has the average RMS deviation of 1.06 °A. The prediction of crystal structures of small organic molecules has significantly improved over the last two decades. Most of the new developments, since the first blind test held in 1999, have occurred in the lattice energy estimation subproblem. In this work, a new efficient systematic search method that avoids random moves is proposed. It systematically searches through the space of possible crystal structures and conducts search space cuts based on statistics collected from the structural databases. It is demonstrated that the fast search method for rigid molecules can be extended to include flexible molecules as well. Also, the results of some prediction experiments are provided showing that in most cases the systematic search generates a structure with less than 1.0°A RMSD from the experimental crystal structure. The scoring function that has been developed for these experiments is described briefly. It is also demonstrated that with a more accurate lattice energy estimation function, better results can be achieved with the proposed robust search method.

In silico ligand docking is a versatile and common technique when predicting ligands and inhibitors for protein binding sites. The various docking programmes aim to calculate binding energies and to predict interactions, thus identifying potential ligands.The currently available programmes lack satisfying means by which to account for structural water molecules which can either mediate protein-ligand contacts or be displaced upon ligand binding. The present project aims to generate data to facilitate the global work of developing scoring functions in docking programmes to account for structural water molecules contribution to ligand binding to fill the said void. This is done by validating the performance of docking using a simple model system (cytochrome C peroxidase (CCP) W191G) containing four well ordered, deeply buried structural water molecules which are known to either interact with a ligand or to be displaced upon ligand binding.Known ligands were docked into eight (crystallographically determined) receptor set-ups comprising the receptor and no, one or two of the water molecules. The performance was validated by comparison of the binding modes of the docked ligands and the crystal structures, comparison of docking scores of the ligands in the different set-ups, enrichment of the ligands from a database of decoys and finally by predicting new ligands from the decoy database. In addition a high resolution crystal structure of CCP W191G in complex with 3-aminopyridine (3AP) was determined in order to resolve ambiguities in the binding mode of this ligand.

Background: Along with the rapid economic development in China, some associatingproblems emerged, such as inflation. Especially for the daily consuming fresh fruits andvegetables (FFV), the price goes up at very fast speed, which draws a lot of publicattention on it. Farmers are discouraged and hurt by the low vegetable prices. However,end consumers are complaining about the high vegetable prices. A consensus is reachedthat the problem behind this phenomenon exists in the "distribution links".Aim: How is the current status of FFV distribution system of supermarkets in China?What factors do influence the efficiency and cost of the system? How is theimplementation of ASD in China and what are the advantages and barriers? Should it beimplemented widely? If yes, what are our recommendations to improve it?Definition: Agricultural super-docking is a new method of supply and distribution offresh agricultural products from farmers to supermarkets directly, by signing anagreement of intent between farmers and merchants, in order to build an efficientplatform for quality agricultural products to enter the supermarkets. The essence of ASDis to dock the thousands of small farmers and the different supermarkets to build anintegrated production and marketing chain to gain benefit for merchants, farmers andconsumers at the same time.Completion and results: It is a complex task to improve the efficiency of FFVdistribution system of supermarkets in China and there is a long way to go to implementASD successfully and widely since this market is at the starting stage and immature. Toimplement ASD successfully and widely, professional FFV third-party distributioncenters should be constructed, as well as exchanging information norm.

The main topic of this thesis is the development of computational search methods that are useful in drug design applications. The emphasis is on exhaustiveness of the search method such that it can guarantee a certain level of geometric accuracy. In particular, the following two problems are addressed: (i) Prediction of binding mode of a drug molecule to a receptor and (ii) prediction of crystal structures of drug molecules. Predicting the binding mode(s) of a drug molecule to a target receptor is pivotal in structure-based rational drug design. In contrast to most approaches to solve this problem, the idea in this work is to analyze the search problem from a computational perspective. By building on top of an existing docking tool, new methods are proposed and relevant computational results are proven. These methods and results are applicable for other place-and-join frameworks as well. A fast approximation scheme for the docking of rigid fragments is described that guarantees certain geometric approximation factors. It is also demonstrated that this can be translated into an energy approximation for simple scoring functions. A polynomial time algorithm is developed for the matching phase of the docked rigid fragments. It is demonstrated that the generic matching problem is NP-hard. At the same time the optimality of the proposed algorithm is proven under certain scoring function conditions. The matching results are also applicable for some of the fragment-based de novo design methods. On the practical side, the proposed method is tested on 829 complexes from the PDB. The results show that the closest predicted pose to the native structure has the average RMS deviation of 1.06 °A. The prediction of crystal structures of small organic molecules has significantly improved over the last two decades. Most of the new developments, since the first blind test held in 1999, have occurred in the lattice energy estimation subproblem. In this work, a new efficient systematic search method that avoids random moves is proposed. It systematically searches through the space of possible crystal structures and conducts search space cuts based on statistics collected from the structural databases. It is demonstrated that the fast search method for rigid molecules can be extended to include flexible molecules as well. Also, the results of some prediction experiments are provided showing that in most cases the systematic search generates a structure with less than 1.0°A RMSD from the experimental crystal structure. The scoring function that has been developed for these experiments is described briefly. It is also demonstrated that with a more accurate lattice energy estimation function, better results can be achieved with the proposed robust search method.

Problem: Since there is not much inside information available, the problem that will be handled by this thesis is the coordination of warehousing activities within the logistics centers put to use by the Olympic Summer Games from 2000 to 2008. A special attention is given to certain requirements such as layout, capacity management, ownership and distribution applications. Purpose: The purpose of this thesis is based on warehouse requirementsand their specific adjustment to the Olympic Summer Games, further emphasizing on distribution applications influencing the capacityand ownership. Theory: The theoretical section touches upon event logistics, the Olympic Games and more importantly, logistics centers as a generic termfor distribution facilities and warehouses. Further, types of warehouses, capacity management, ownership and distribution applications are examined in order to be able to compare the various Games. Method: The method for this research is based on a case study conducted by semi-structured interviews with several people involved in the logistics organization of the Games. All interviews are conducted over the telephone and analyzed accordingly. However, secondary data was of high importance due to the limited number of interview respondents. Conclusion: All analyzed features of a warehouse facility had to be more efficiently and effectively performed in order to serve the great approach for the Olympic Summer Games. The implementation of distribution applications was not sophisticated enough to benefit capacity savings. The leased ownership situation and outsourcing to third party logistics providers were advantageous, but did not further influence the planning and utilization phase of the Olympic Games.

Docking is one of the methods in virtual screeing. Studies from around 1980 to now, many docking software have been developed, but these software have many short comings. The software currently used for docking have many disadvantage: poor efficiency, rigid structure of the proteins and the ligands, poor accuracy, without the polarization after binding, leading virtual screening is still stuck in a supporting role. Our experiment with new method improves those shortcomings of docking. With this new method, we obtain the following improvements in docking process: better efficiency, flexible structure of the proteins and the ligands, better accuracy. In the depression-related protein docked with traditional Chinese medicine test. We change the conformations of ligands with the shapes of active sites before posing, this makes the conformation of complex much more reasonable, even more complicated, large ligands. In the experiment of random sites docking, we found a possible path for compounds traveling into active sites. We illustrate a docking area by linking all possible docking sites. The lead compound may not successfully travel into active site when this area is occupied by other proteins or ligands. In the docking experiment with side-chain rotation, we rotate the torsion angle to make side chains relax. We obtained a similar result with molecular dynamics, and saved a lot of time.