Virtual fragment screening on GPCRs: A case study on dopamine D3 and histamine H4 receptors

Prospective structure based virtual fragment screening methodologies on two GPCR targets namely the dopamine D3 and the histamine H4 receptors with a library of 12,905 fragments were evaluated. Fragments were docked to the X-ray structure and the homology model of the D3 and H4 receptors, respectively. Representative receptor conformations for ensemble docking were obtained from molecular dynamics trajectories. In vitro confirmed hit rates ranged from 16% to 32%. Hits had high ligand efficiency (LE) values in the range of 0.31-0.74 and also acceptable lipophilic efficiency. The X-ray structure, the homology model and structural ensembles were all found suitable for docking based virtual screening of fragments against these GPCRs. However, there was little overlap among different hit sets and methodologies were thus complementary to each other. (C) 2014 Elsevier Masson SAS. All rights reserved

Site-Directed Mutagenesis Of Conserved Amino Acids Residues In N5-Carboxyaminoimidazole Ribonucleotide Mutase: Converting N5-Cair Mutase Into Aminoimidazole Ribonnucleotide Carboxylase & Developing A High-Throughput Screening Assay For The Discovery Of N5-Carboxyaminoimidazole Ribonucleotide Mutase

The de novo purine biosynthesis pathway plays a critical role in providing new purines to the cell. Previous studies have shown differences between the human and bacterial pathways which suggests that pathway may be a potential target for antibiotic drug discovery. Three critical enzymes are involved in the pathway divergence. In the bacterial pathway, N5-CAIR synthetase (PurK) first converts AIR to N5-CAIR, which is then transformed into CAIR catalyzed by the enzyme N5-CAIR mutase (Class I PurE). In the human pathway, AIR carboxylase (Class II PurE) catalyzes the direct conversion of AIR to CAIR. Class I and Class II PurEs have structure and sequence similarities but also are functionally different. However, the residues responsible for these differences are unknown. In this study, we hypnotized that the class-specific conserved residues in the active site might be the key to determining the functional differences between the two PurEs. Site-directed mutagenesis was used to convert residues of Class I PurEs to Class II PurEs. Several mutant PurEs were made and examined for CO2-dependent conversion of AIR to CAIR. Two mutants H71A and H71G displayed CO2 dependent that was similar to that observed for AIR carboxylase. Additional studies revealed that these enzymes also were capable of using N5-CAIR as a substrate. This indicates that the H71A and H71G mutant have AIR carboxylase as well as N5-CAIR mutase activity. Examination of the crystal structure of N5-CAIR mutase indicates that His71 is at the bottom of the active site and removal of this residue creates a channel between active sites in two subunits. We speculate that this channel may be key for the utilization of CO2

Fragment-Based Drug Discovery Using a Multidomain, Parallel MD-MM/PBSA Screening Protocol

We have developed a rigorous computational screening protocol to identify novel fragment-like inhibitors of N⁵-CAIR mutase (PurE), a key enzyme involved in de novo purine synthesis that represents a novel target for the design of antibacterial agents. This computational screening protocol utilizes molecular docking, graphics processing unit (GPU)-accelerated molecular dynamics, and Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) free energy estimations to investigate the binding modes and energies of fragments in the active sites of PurE. PurE is a functional octamer comprised of identical subunits. The octameric structure, with its eight active sites, provided a distinct advantage in these studies because, for a given simulation length, we were able to place eight separate fragment compounds in the active sites to increase the throughput of the MM/PBSA analysis. To validate this protocol, we have screened an in-house fragment library consisting of 352 compounds. The theoretical results were then compared with the results of two experimental fragment screens, Nuclear Magnetic Resonance (NMR) and Surface Plasmon Resonance (SPR) binding analyses. In these validation studies, the protocol was able to effectively identify the competitive binders that had been independently identified by experimental testing, suggesting the potential utility of this method for the identification of novel fragments for future development as PurE inhibitors

A Step Closer to Precision Oncology: Computational, Biochemical, and Cell-Based Screening to Find Compounds that Stabilize p53

Personalized medicine in cancer aims to tailor a treatment plan that takes into account the unique features of a patient's malignancy. One therapeutic target that has a chance to affect a large population of cancer patients is p53. p53 is a tumor suppressor that activates senescence or apoptosis in cells that have accumulated mutations that could lead to cancer. Half of all cancers have mutations in p53, which highlights the importance of its role in disease. A subset of these mutations have been shown to inhibit p53 function by destabilizing p53's core domain. This led to the hypothesis that a personalized drug for patients with this type of destabilized p53 mutation could lead to apoptosis in cancer cells. There has been a lot of evidence supporting this hypothesis. This evidence has inspired many researchers to screen for small molecules that stabilize p53 mutants and rescue function. However, the hits discovered in these screens (with one potential exception) have not been found to be adequate drug leads for several reasons. Many have turned out to rescue function, but not by directly binding p53. Others bind p53, but either lack sufficient binding affinity or cause nonspecific cell responses. All of these are likely to induce side effects if used as part of a cancer therapeutic. This leads to the question: Is there a better way to find a small molecule stabilizer for cancer-associated mutants of p53? Here, I present an alternative approach that focuses on finding a direct binder to p53's core domain in order to avoid off-target effects. Our initial step was a computational approach that uses the crystal structure of p53's core domain in order to virtually screen a set of small molecules for binding. I found a novel pocket on the protein structure that I predicted to be druggable, because the site readily forms pockets during simulations of the core domain. I performed a virtual screen using the DARC, a docking tool from the molecular modeling suite, Rosetta, and selected the 28 best ranked compounds for biochemical testing with purified p53 using two different cancer-associated, destabilizing mutations. Surprisingly, I found that 11 of the 28 compounds stabilized both mutants. Further testing was done in cancer cell lines showing that 7 compounds activated p53 transcription of p21 and PUMA, which are known targets of p53. Using the fluorescent antibody pAb 1620 that binds natively folded p53, we showed that 4 of the compounds lead to a much higher concentration of folded p53 in cells. The excitingly high hit rate was found from a modest sized initial virtual screen of only 64,000 molecules. This suggests that this novel pocket is prone to bind molecules in a manner that rescues structure and function, and should be as a starting point for a larger screen. Also, the compounds from the current screen are intriguing hits that will be further analyzed and optimized to develop new stabilizers of p53

Computational modeling of protein ligand systems

Biomoleküle können auf Basis ihrer Struktur, ihrer Dynamik oder der von ihnen eingegangenen Wechselwirkungen bzw. Funktion betrachtet werden. Die drei klassischen Verfahren der biomolekularen Modellierung, die für solche Untersuchungen verwendet werden sind die Homologie Modellierung, das Docking unddie Molekulardynamiksimulation (MD). In dieser Promotionsarbeit sollen diese drei Verfahren etabliert, angewendet und mit anderen Verfahren, wie elektrostatischen Modellen, Signifikanzanalysen, Clusteranalysen und Varianten der Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) Methode, weiterentwickelt werden, um die nachfolgenden Fragestellungen in drei biomolekularen Systemen zu untersuchen. Im ersten Fall werden verschiedene Glucose Dehydrogenase Isoenzyme des hyperthermophilen Archaeon Sulfolobus solfataricus untersucht und ihre Substratspezifität wird miteinander verglichen. Das Basisverfahren ist hier die Homologie Modellierung. Sie wird durch ein elektrostatisches Modell und ein Docking erweitert, um ein tieferes Verständnis ihrer Wechselwirkungen mit den Substraten zu erhalten. Im zweiten Fall wird die Chitinase B des Enterobakteriums Serratia marcescens mit bekannten Inhibitoren untersucht. Hier bildet das Docking die Grundlage und wird unter anderem mit dem MMPBSA Methode erweitert. Im letzten Fall werden verschiedene SH3 Domänen mit ihren Peptidliganden mittels MD untersucht. Die Simulationen werden dabei mit Signifikanzanalysen statistisch verglichen und geclustert. Daraus ergeben sich Strukturmodelle, die mit höherer Wahrscheinlichkeit zutreffen als Modelle, die mit gängigen Verfahren erzeugt werden.Biomolecules can be analyzed with regard to their structure, dynamics, interactions, and function. Three standard methods for the analysis of these molecules are homology modeling, docking, and molecular dynamics (MD) simulation. In this dissertation, these three methods are established, tested and combined with additional techniques, such as electrostatic models, significance analysis, cluster analysis, and variants of the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method. I examine with these computational modeling methods three biomolecular systems: First, various glucose dehydrogenase isoenzymes of the hyperthermophilic archaeon Sulfolobus solfataricus are studied and their respective substrate specificity are compared. Here, the main method is homology modeling. It is enhanced by electrostatic models and docking in order to obtain a deeper understanding of the interactions between enzymes and ligands. Second, chitinase B of the enterobacterium Serratia marcescens is investigated, including its interactions with known inhibitors. The results from an initial docking simulations are refined by subsequent calculations with the MMPBSA method. Third, different SH3 domains are examined in complex with their peptide ligands by MD simulations. The simulations are compared statistically with a significance analysis method and clustering. The outcome of these analyses promise to be more realistic models than models developed by conventional methods

A Comparison of Functionally Divergent Forms of the Purine Biosynthesis Enzyme PurE.

Purines are the basic building block for essential biomolecules such as DNA, RNA, NADH, CoA, and several essential vitamin cofactors. Most organisms have the ability to synthesize purines through the de novo purine biosynthesis pathway