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Probing natural molecules with PPAR- to reveal potent agonist against Cancer
Špaková, Adriána ; Bhogal, Inderjeet (referee) ; Roy, Sudeep (advisor)
Práca sa zaoberá hľadaním prírodnej molekuly s potenciálnymi agonistickými vlastnosťami proti rakovine. Cieľom práce bolo predovšetkým pochopiť súvislosť medzi receptorom PPAR- a rakovinou. Následne boli molekuly zo šiestich databáz virtuálne skrínované a dokované k nukleárnemu receptoru PPAR- za využitia počítačom podporovaného dizajnu liečiv. Najlepšie molekuly podstúpili ďalšie preskúmanie, vrátane dynamickej simulácie a štúdie viazania voľnej energie. Overenie bezpečnosti najlepších molekúl bolo vykonané predikčnými modelmi ADMET. Dôležitou súčasťou práce bolo porovnanie novoobjavených molekúl disponujúcich agonistickými vlastnosťami proti rakovine s už známymi na trhu. Konkrétne Troglitazón a Rosiglitazón slúžili ako štandardy, ktoré sa vyznačujú vysokou afinitou k receptoru PPAR- a prejavili antineoplastické účinky v rôznych ľudských malígnych nádoroch, vrátane rakoviny prsníka, hrubého čreva a pankreasu. Na druhej strane, tieto dve syntetické molekuly čelia varovaniu zo strany FDA (Úrad pre potraviny a liečivá) v dôsledku ich nepriaznivých vedľajších účinkov. V rámci práce sa podarilo objaviť prírodné molekuly, ktoré vykázali lepšie vlastnosti ako aktuálne štandardy. Tieto sľubné výsledky si zaslúžia ďalšiu pozornosť. Jedna z molekúl by mohla potenciálne viesť k vývoju nového lieku.
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Modeling of fragment-based molecular similarity
Lamprecht, Matyáš ; Škoda, Petr (advisor) ; Mráz, František (referee)
Virtual screening is a part of computer-aided drug design, which aims to identify biologically active molecules. The ligand-based virtual screening employs known bio- logically active molecules and similarity search. A common approach to computation of molecular similarity is to utilize molecular fingerprints. Hashed structural molecular fingerprints hash fragments (subgraphs) of molecular graphs into a bit string reducing the problem of molecular similarity to the bit string similarity. Due to the hashing two distinct fragments may collide, which causes information loss. For this reason collisions are considered unwanted and they are generally believed to decrease a performance. Our goal was, contrary to the general believe, test whether collisions can have positive impact on the performance. For this purpose we designed several similarity models based on fragments. In order to make testing and evaluation easy we implemented testing environ- ment. Results of our experiments prove that some collisions can outperform commonly used methods. Moreover some collisions in a specific model can lead to a performance of AUC over 0.99. 1
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Utilization of latent semantic analysis in virtual screening
Kolář, Jiří ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Title: Utilization of latent semantic analysis in virtual screening Author: Jiří Kolář Department: Department of Software Engineering Supervisor: RNDr. David Hoksza, Ph.D., Department of Software Engineering Abstract: Aim of this thesis is to investigate utilisation of latent semantic in- dexing in Virtual screening. We have examined existing VS method called lat- ent semantic structural indexing (LaSSI) and compared performance of different structural fingerprints. Additionally, we have developed a new model that com- pare fragments of molecules by usage of latent semantic indexing. Fragments are characterized by formula based counts and descriptors describing the physi- cochemical properties. Results of our methods are compared to VS techniques using directly standard fingerprints. Keywords: virtual screening cheminformatics ligand-based fingerprints ECFP TT latent semantic analysis LaSSI iii
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Využití simulovaného žíhání pro optimalizaci molekulárních otisků ve virtuálním screeningu
Filandr, Adam ; Hoksza, David (advisor) ; Kratochvíl, Miroslav (referee)
Ligand based virtual screening can be realised with various molecular rep- resentations. Fragment-feature representation represents the molecules as a set of fragments, where each fragment receives a set of descriptors. First goal of this thesis is to find suitable similarity function for such represen- tation. This representation can also be improved by assigning a weight for each descriptor, which gives it a priority in a given similarity function. The second goal of this thesis is to examine simulated annealing as an algorithm used to find the weights. We experimentally analysed the influence of various fragment types, descriptor types, similarity functions, correlated descriptors, fragment noise and parameters of simulated annealing. Because the experi- ments are computationally demanding, we also created a tool for large scale computations. 1
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Graph-based molecular representation and its utilization in virtual screening
Šťastná, Aneta ; Hoksza, David (advisor) ; Kopecký, Michal (referee)
Graphs are natural way of representing molecules. However, graph representations and algorithms are not being used for finding similarity of molecules in virtual screening. In this work we test the graph-based methods in ligand-based virtual screening. The similarity of molecular graphs is determined by maximum common subgraph and graph edit distance. We use implementations fmcs from chemoinformatic library RDKit for maximum common subgraph and GraphMatchingToolkit from K.Riesen to determine graph edit distance. We have found suitable combinations of parameters for aplication in ligand-based virtual screening. The results suggest that performance of graph based methods is comparable to the state-of-the-art methods.
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Utiliziation of uncorrelated multi-point pharmacophores in virtual screening
Mička, Ondřej ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Recently, a new method for ligand based virtual screening was published. It uses pharmacophore fingerprints and statistical methods to create a phar- macophore model which is then used to predict the activity of ligands. In this thesis two possible enhancemets of this method were examined. The first one is the removal of correlated pharmacophores, the second one is the utilization of larger pharmacophores (originally only 3-point pharmacopho- res were used). Both modifications were implemented along with neccessary extension of the RDKit cheminformatics toolkit. Finally, both modifications were experimentally evaluated and compared to the original method. Based on the results, combination of the pharmacophore model with the fingerprint similarity was proposed as another modification and evaluated. 1
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