Emerging Chemical Patterns for Virtual Screening and Knowledge Discovery

The adaptation and evaluation of contemporary data mining methods to chemical and biological problems is one of major areas of research in chemoinformatics. Currently, large databases containing millions of small organic compounds are publicly available, and the need for advanced methods to analyze these data increases. Most methods used in chemoinformatics, e.g. quantitative structure activity relationship (QSAR) modeling, decision trees and similarity searching, depend on the availability of large high-quality training data sets. However, in biological settings, the availability of these training sets is rather limited. This is especially true for early stages of drug discovery projects where typically only few active molecules are available. The ability of chemoinformatic methods to generalize from small training sets and accurately predict compound properties such as activity, ADME or toxicity is thus crucially important. Additionally, biological data such as results from high-throughput screening (HTS) campaigns is heavily biased towards inactive compounds. This bias presents an additional challenge for the adaptation of data mining methods and distinguishes chemoinformatics data from the standard benchmark scenarios in the data mining community. Even if a highly accurate classifier would be available, it is still necessary to evaluate the predictions experimentally. These experiments are both costly and time-consuming and the need to optimize resources has driven the development of integrated screening protocols which try to minimize experimental efforts but still reaching high hit rates of active compounds. This integration, termed “sequential screening” benefits from the complementary nature of experimental HTS and computational virtual screening (VS) methods. In this thesis, a current data mining framework based on class-specific nominal combinations of attributes (emerging patterns) is adapted to chemoinformatic problems and thoroughly evaluated. Combining emerging pattern methodology and the well-known notion of chemical descriptors, emerging chemical patterns (ECP) are defined as class- specific descriptor value range combinations. Each pattern can be thought of as a region in chemical space which is dominated by compounds from one class only. Based on chemical patterns, several experiments are presented which evaluate the performance of pattern-based knowledge mining, property prediction, compound ranking and sequential screening. ECP-based classification is implemented and evaluated on four activity classes for the prediction of compound potency levels. Compared to decision trees and a Bayesian binary QSAR method, ECP-based classification produces high accuracy in positive and negative classes even on the basis of very small training set, a result especially valuable to chemoinformatic problems. The simple nature of ECPs as class-specific descriptor value range combinations makes them easily interpretable. This is used to related ECPs to changes in the interaction network of protein-ligand complexes when the binding conformation is replaced by a computer-modeled conformation in a knowledge mining experiment. ECPs capture well-known energetic differences between binding and energy-minimized conformations and additionally present new insight into these differences on a class level analysis. Finally, the integration of ECPs and HTS is evaluated in simulated lead-optimization and sequential screening experiments. The high accuracy on very small training sets is exploited to design an iterative simulated lead optimization experiment based on experimental evaluation of randomly selected small training sets. In each iteration, all compounds predicted to be weakly active are removed and the remaining compound set is enriched with highly potent compounds. On this basis, a simulated sequential screening experiment shows that ECP-based ranking recovers 19% of available compounds while reducing the “experimental” effort to 0.2%. These findings illustrate the potential of sequential screening protocols and hopefully increase the popularity of this relatively new methodology

Analyzing GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

G-protein-coupled receptors (GPCRs) have enormous physiological and biomedical importance, and therefore it is not surprising that they are the targets of many prescribed drugs. Further progress in GPCR drug discovery is highly dependent on the availability of protein structural information. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanics (QM) approaches are often too computationally expensive to be of practical use in time-sensitive situations, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed, and the ability to reveal key interactions that would otherwise be hard to detect. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule toward ligand binding, including an analysis of their chemical nature. Such information is essential for an efficient structure-based drug design (SBDD) process. In this chapter, we describe how to use FMO in the characterization of GPCR-ligand interactions

Characterizing Rhodopsin-Arrestin Interactions with the Fragment Molecular Orbital (FMO) Method

Arrestin binding to G protein-coupled receptors (GPCRs) plays a vital role in receptor signaling. Recently, the crystal structure of rhodopsin bound to activated visual arrestin was resolved using XFEL (X-ray free electron laser). However, even with the crystal structure in hand, our ability to understand GPCR-arrestin binding is limited by the availability of accurate tools to explore receptor-arrestin interactions. We applied fragment molecular orbital (FMO) method to explore the interactions formed between the residues of rhodopsin and arrestin. FMO enables ab initio approaches to be applied to systems that conventional quantum mechanical (QM) methods would be too compute-expensive. The FMO calculations detected 35 significant interactions involved in rhodopsin-arrestin binding formed by 25 residues of rhodopsin and 28 residues of arrestin. Two major regions of interaction were identified: at the C-terminal tail of rhodopsin (D330-S343) and where the "finger loop" (G69-T79) of arrestin directly inserts into rhodopsin active core. Out of these 35 interactions, 23 were mainly electrostatic and 12 hydrophobic in nature

The Effective Fragment Molecular Orbital Method for Fragments Connected by Covalent Bonds

We extend the effective fragment molecular orbital method (EFMO) into treating fragments connected by covalent bonds. The accuracy of EFMO is compared to FMO and conventional ab initio electronic structure methods for polypeptides including proteins. Errors in energy for RHF and MP2 are within 2 kcal/mol for neutral polypeptides and 6 kcal/mol for charged polypeptides similar to FMO but obtained two to five times faster. For proteins, the errors are also within a few kcal/mol of the FMO results. We developed both the RHF and MP2 gradient for EFMO. Compared to ab initio, the EFMO optimized structures had an RMSD of 0.40 and 0.44 {\AA} for RHF and MP2, respectively.Comment: Revised manuscrip

Design, Synthesis and Cytotoxic Activity of Novel 2,3-disubstituted Pyrazine Derivatives

Pyrazine derivatives possess numerous pharmacological effects including but not limited to antiviral, antibiotic, antifungal, diuretic, anticonvulsant, antidiabetic, analgesic and anti proliferative effect. Consequently, interest has been shown by researchers in the field of pyrazine-based drug synthesis and many of the synthesized derivatives succeeded to reach the clinical field. A promising research discipline was concerned in utilizing the antiproliferative and cytotoxic activity of pyrazine derivatives -that is attributed to various mechanisms one of which is protein kinase inhibition- in designing new anti-cancer agents. In this study a set of disubstituted pyrazine derivatives has been designed and synthesized through a sequential nucleophilic substitution of chlorine atoms of 2,3-dichloropyrazine with amines or other nucleophiles. The synthesized derivatives were purified using several chromatographic techniques, and characterized by (1H-NMR, 13C-NMR, FT-IR, and MS (ESI)) spectroscopy. The mono-substituted pyrazine derivative A-7 (7) and three of its disubstituted analogues (YAN1(18), YAN-2 (19), and YAN-3(20)) were in vitro screened for their biological activity against two forms of acute myeloid leukemia cells (Molm-13). The viability of the cells was determined using WST-1 assay. Initial results of the tested derivatives showed that A-7 (7) was more potent than its analogues with IC50 of 18 and 39 µM against Molm-13 (sh-p53) and Molm-13 (empty vector) respectivelyThe biological activity of mono and disubstituted pyrazine derivatives was predicted using PASS software. Initial results demonstrated that A13 (13), A14 (14), YAN-7 (24), and YAN-8 (25) exhibited predicted activities as antineoplastic agents and signal transduction pathway inhibitors with relatively high Pa values. The previously mentioned compounds shared also the same mechanism of action “protein kinase inhibitor” with Pa values larger than 0.8SAR derived from PASS and initial biological activity screening results proved that the activity of the synthesized derivative is highly affected by the site and type of the substituent on the pyrazine ring. 2,3-disubstituted derivatives showed better Pa values when compared to the corresponding 2,5-disubstituted ones. In addition, amine substituents at positions 2 and 3 of pyrazine ring were preferred over alkoxide substituents in terms of antineoplastic activity. It was noticed that 1-(5-trifluoromethylpyridin-2-yl)-piperazine and 2-aminopyridine pharmacophores were the most active amine substituents. In order to gain an insight into the binding mode of pyrazine derivatives with CDK-2, a series of sixteen derivatives were docked with inactive monomeric cyclin dependent kinase-2 using SwissDock software. Results were compared with ‘Aloisine B‟, a well-known CDK-2 inhibitor. In terms of binding mode, pyrazine derivatives occupied the CDK-2 ATP binding site and made hydrogen bonds to the kinase backbone within the hinge sequence that links the two lobes of the kinase. The docked derivatives exhibited different binding affinities to the target, YAN-8 (25) showed the highest full fitness value (-1422.14 kcal/mol) among the synthesized derivatives. Moreover, both the full fitness and energy values indicated that YAN-8 (25) has higher affinity to the target in comparison to the known inhibitor Aloisine B (-1406.92 kcal/mol). Finally, the concept of drug likeness of the synthesized derivatives was investigated using the rule of five. Results revealed that all of the tested derivatives successfully met the rule of 5requirements except YAN-9 (26) and YAN-10 (27) which possessed molecular weights larger than 500 Daltons.

Promising 2,6,9-Trisubstituted Purine Derivatives for Anticancer Compounds: Synthesis, 3D-QSAR, and Preliminary Biological Assays

We designed, synthesized, and evaluated novel 2,6,9-trisubstituted purine derivatives for their prospective role as antitumor compounds. Using simple and efficient methodologies, 31 compounds were obtained. We tested these compounds in vitro to draw conclusions about their cell toxicity on seven cancer cells lines and one non-neoplastic cell line. Structural requirements for antitumor activity on two different cancer cell lines were analyzed with SAR and 3D-QSAR. The 3D-QSAR models showed that steric properties could better explain the cytotoxicity of compounds than electronic properties (70% and 30% of contribution, respectively). From this analysis, we concluded that an arylpiperazinyl system connected at position 6 of the purine ring is beneficial for cytotoxic activity, while the use of bulky systems at position C-2 of the purine is not favorable. Compound 7h was found to be an effective potential agent when compared with a currently marketed drug, cisplatin, in four out of the seven cancer cell lines tested. Compound 7h showed the highest potency, unprecedented selectivity, and complied with all the Lipinski rules. Finally, it was demonstrated that 7h induced apoptosis and caused cell cycle arrest at the S-phase on HL-60 cells. Our study suggests that substitution in the purine core by arylpiperidine moiety is essential to obtain derivatives with potential anticancer activityFinancial support was received from FONDECYT (Research Grant N◦ 1161816) and FONDEQUIP program CONICYT EQM 160042, Czech Science Foundation (19-09086S) and Palacky University (IGA_PrF_2019_013) and Xunta de Galicia (ED431C 2018/21) and European Regional Development Fund (Project ENOCH, N◦ CZ.02.1.01/0.0/0.0/16_019/0000868)S

Characterization and Quantification of Covalent Modification of Proteins Using Mass Spectrometry

Identification and characterization of various post-translational modifications of protein is a key to understanding many unknown cellular processes. In the last few decades, mass spectrometry has evolved as an essential and effective analytical tool for qualitative and quantitative analysis of proteins. In this research, we have developed a novel MALDI-MS2 based quantification method for Desmosine and Isodesmosine, which served as cross-linking amino acids of elastin, in order to measure the elastin degradation in the body. This is the first quantification method that not only illustrates the potential of MALDI-Ion Trap MS2, but also improvement over the current LC-MS method, in terms of analysis time and solvent consumption, while maintaining similar analytical characteristics. The method is utilized to evaluate the time-dependent degradation of Des upon UV radiation (254nm) and result found to be consistent with quantification by 1H NMR. This work also involves the investigation of potential phosphorylation sites and evaluation of its role in various biochemical processes during HIV infection. Based on the results from different phosphorylation prediction algorithms, many in-vitro kinase assays were performed on HIV-derived peptides/proteins in presence of potential kinases. We have successfully identified few novel interactions between host-kinases/HIV phosphorylation substrates. These include the interactions of phosphorylation sites of Vif, Nef and Capsid proteins with protein kinase C (PKC), protein kinase A (PKA), and p38 MAPK respectively. Moreover, this work includes the development of cell-active inhibitors for cysteine cathepsins, a class of enzymes involve in many important cellular processes and in various disorders. In this study, we have synthesized library of two different classes of molecules containing oxirane and vinylsulfonate moieties. Various cell-based experiments were conducted to successfully demonstrate intracellular inhibition of cysteine cathepsin by these developed inhibitory molecules. The result of our study shows 2-(2-ehtylphenylsulfonyl) oxirane is cell-permeable and irreversible inhibitor of cathepsin B. On the other hand, peptidyl vinylsulfonate inhibitor (KD-1) is highly potent and selective cathepsin L inhibitor

Doctor of Philosophy

dissertationThe dysregulation of proteinâ€"protein interaction (PPI) networks has been implicated in many diseases. Designing therapeutic small-molecule inhibitors of these interactions is a challenging field for medicinal chemistry. This work advances the techniques for discovering more potent PPI inhibitors through integration of computational and biochemical techniques. High-throughput screening using fluorescence polarization and AlphaScreen assays identified an acyl hydrazone-containing inhibitor of the β-catenin/Tcf4 PPI, a key mediator of the canonical Wnt signaling pathway. By removing the undesirable acyl hydrazone moiety, a new compound, 4-(5H-[1,2,5]oxadiazolo[3',4':5,6]pyrazino[2,3-b]indol-5-yl)butanoic acid, was developed to selectively inhibit the β-catenin/Tcf4 interaction. The ethyl ester of this compound was tested in zebrafish embryos and shown to inhibit Wnt signaling in vivo at 2 and 10 μM concentrations. Differences between the PPI interface and the active site of traditional targets add to the difficulty of discovering PPI inhibitors. Herein, the relationship between inhibitor potency and ligand burialâ€"defined as the fraction of the solvent accessible surface areas of the bound over unbound ligand, θlâ€"in the PPI surface was evaluated. A positive correlation between θl and inhibitor potency was discovered. However, this correlation was secondary to the strong nonbonding interactions. A study of five PPI targets with corresponding inhibitor-bound crystal structures also revealed that empirical scoring functions were slightly better at identifying known inhibitors out of the putatively inactive test set, and the Lamarckian genetic algorithm was more successful at pose prediction. Due to the nature of the PPI surface, directly targeting the binding site may be difficult. A novel combination of computational methods explored the druggability, selectivity, and potential allosteric regulation of PPIs. Solvent mapping confirmed that Tcf4, E-cadherin, APC and axin use the same binding site on β-catenin in different ways. Evolutionary trace analysis indicated that the region surrounding W504 of β-catenin might be a potentially allosteric site. Site-directed mutagenesis testing results for a W504I β-catenin mutant resulted in three-fold increased binding of Tcf4 to β-catenin over the wild-type. This new site is promising for the discovery of future allosteric inhibitors of the β-catenin/Tcf4 PPI. The combined results from these studies reveals ways to better design PPI inhibitors