Applications of Systematic Molecular Scaffold Enumeration to Enrich Structure-Activity Relationship Information.

Establishing structure-activity relationships (SARs) in hit identification during early stage drug discovery is important in accelerating hit confirmation and expansion. We describe the development of EnCore, a systematic molecular scaffold enumeration protocol using single atom mutations, to enhance the application of objective scaffold definitions and to enrich SAR information from analysis of high-throughput screening output. A list of 43 literature medicinal chemistry compound series, each containing a minimum of 100 compounds, published in the Journal of Medicinal Chemistry was collated to validate the protocol. Analysis using the top representative Level 1 scaffolds this list of literature compound series demonstrated that EnCore could mimic the scaffold exploration conducted when establishing SAR. When EnCore was applied to analyze an HTS library containing over 200 000 compounds, we observed that over 70% of the molecular scaffolds matched extant scaffolds within the library after enumeration. In particular, over 60% of the singleton scaffolds with only one representative compound were found to have structurally related compounds after enumeration. These results illustrate the potential of EnCore to enrich SAR information. A case study using literature cyclooxygenase-2 inhibitors further demonstrates the advantage of EnCore application in establishing SAR from structurally related scaffolds. EnCore complements literature enumeration methods in enabling changes to the physicochemical properties of molecular scaffolds and structural modifications to aliphatic rings and linkers. The enumerated scaffold clusters generated would constitute a comprehensive collection of scaffolds for scaffold morphing and hopping

Novel approaches in cancer management with circulating tumor cell clusters

© 2019 The Authors Tumor metastasis is responsible for the vast majority of cancer-associated morbidities and mortalities. Recent studies have disclosed the higher metastatic potential of circulating tumor cell (CTC) clusters than single CTCs. Despite long-term study on metastasis, the characterizations of its most potent cellular drivers, i.e., CTC clusters have only recently been investigated. The analysis of CTC clusters offers new intuitions into the mechanism of tumor metastasis and can lead to the development of cancer diagnosis and prognosis, drug screening, detection of gene mutations, and anti-metastatic therapeutics. In recent years, considerable attention has been dedicated to the development of efficient methods to separate CTC clusters from the patients’ blood, mainly through micro technologies based on biological and physical principles. In this review, we summarize recent developments in CTC clusters with a particular emphasis on passive separation methods that specifically have been developed for CTC clusters or have the potential for CTC cluster separation. Methods such as liquid biopsy are of paramount importance for commercialized healthcare settings. Furthermore, the role of CTC clusters in metastasis, their physical and biological characteristics, clinical applications and current challenges of this biomarker are thoroughly discussed. The current review can shed light on the development of more efficient CTC cluster separation method that will enhance the pivotal understanding of the metastatic process and may be practical in contriving new strategies to control and suppress cancer and metastasis

Chemogenomic Analysis of the Druggable Kinome and Its Application to Repositioning and Lead Identification Studies

Owing to the intrinsic polypharmacological nature of most small-molecule kinase inhibitors, there is a need for computational models that enable systematic exploration of the chemogenomic landscape underlying druggable kinome toward more efficient kinome-profiling strategies. We implemented Virtual-KinomeProfiler, an efficient computational platform that captures distinct representations of chemical similarity space of the druggable kinome for various drug discovery endeavors. By using the computational platform, we profiled approximately 37 million compound-kinase pairs and made predictions for 151,708 compounds in terms of their repositioning and lead molecule potential, against 248 kinases simultaneously. Experimental testing with biochemical assays validated 51 of the predicted interactions, identifying 19 small-molecule inhibitors of EGFR, HCK, FLT1, and MSK1 protein kinases. The prediction model led to a 1.5-fold increase in precision and 2.8-fold decrease in false-discovery rate, when compared with traditional single-dose biochemical screening, which demonstrates its potential to drastically expedite the kinome-specific drug discovery process.Peer reviewe

The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching

open access articleBackground: The Chemistry Development Kit (CDK) is a widely used open source cheminformatics toolkit, providing data structures to represent chemical concepts along with methods to manipulate such structures and perform computations on them. The library implements a wide variety of cheminformatics algorithms ranging from chemical structure canonicalization to molecular descriptor calculations and pharmacophore perception. It is used in drug discovery, metabolomics, and toxicology. Over the last 10 years, the code base has grown significantly, however, resulting in many complex interdependencies among components and poor performance of many algorithms. Results: We report improvements to the CDK v2.0 since the v1.2 release series, specifically addressing the increased functional complexity and poor performance. We first summarize the addition of new functionality, such atom typing and molecular formula handling, and improvement to existing functionality that has led to significantly better performance for substructure searching, molecular fingerprints, and rendering of molecules. Second, we outline how the CDK has evolved with respect to quality control and the approaches we have adopted to ensure stability, including a code review mechanism. Conclusions: This paper highlights our continued efforts to provide a community driven, open source cheminformatics library, and shows that such collaborative projects can thrive over extended periods of time, resulting in a high-quality and performant library. By taking advantage of community support and contributions, we show that an open source cheminformatics project can act as a peer reviewed publishing platform for scientific computing software

Dimensions of Antarctic microbial life revealed through microscopic, cultivation-based, molecular phylogenetic and environmental genomic characterization

Extreme cold temperatures have shaped Antarctic environments and the life that lives within them. Microorganisms affiliated with the three domains of life - Bacteria, Archaea, and Eukaryote - can be found in Antarctic environments from deep subglacial lakes to dry deserts and from deep oceans to cold and dark winter surface seawaters. This dissertation focused on the investigation of the microbial assemblage in two Antarctic environments: Lake Vida, located in the McMurdo Dry Valleys, and the surface seawater from the Antarctic Peninsula. Lake Vida has a thick (27+ m) ice cover which seals a cryogenic brine reservoir within the lake ice below 16 m. This brine's environment challenges the conditions for the existence of life. Despite the perceived challenges of aphotic, anoxic and freezing conditions, the brine contained an abundant assemblage (6.13 ± 1.65 × 107 cells mL-1) of ultra-small cells 0.192 ± 0.065 μm in diameter and a less abundant assemblage (1.47 ± 0.25 × 105 cells mL-1) of microbial cells ranging from > 0.2 to 1.5 μm in length. Scanning electron microscopy provided supporting evidence for cell membranes associated with the ~ 0.2 μm cells and helped discern a second smaller size class of particles (0.084 ± 0.063 μm). 16S rRNA clone library analyses indicated that the ultra-small cell-size assemblage was dominated by the Proteobacteria-affiliated genera Herbaspirillum, Pseudoalteromonas, and Marinobacter. Cultivation efforts of the 0.1 - 0.2 μm size fraction led to the isolation of Actinobacteria-affiliated genera Microbacterium and Kocuria. Based on phylogenetic relatedness and microscopic observations, we hypothesize that the ultra-small cells in Lake Vida brine are ultramicrocells that are likely in a reduced size state as a result of environmental stress or life-cycle related conditions. The previously unexplored deeper ice of Lake Vida (from 18 to 27 m) revealed an ice column banded by sediment layers up to 15 cm in length and a diverse and cell-rich microbial assemblage with cell counts ranging from 3.73 × 104 to 8.58 × 106 cells mL-1. Illumina tag sequencing (iTag) targeting the 16S rRNA gene and RNA (as cDNA) indicated that the microbial assemblage from the lake ice and four sediment layers below 21 m was dominated by organisms capable of the reduction and oxidation of sulfur compounds in addition to high molecular weight complex polymer degradation. Proteobacteria, Bacteroidetes, Actinobacteria, and Firmicutes-affiliated genera were the most abundant bacterial phyla detected. The distribution of the microbial assemblage within the ice and sediment layers was correlated with the presence of sediment particles, total dissolved solids (TDS), total carbon, SO42-, and Na+ concentration. Chemolithoautotrophic and heterotrophic genera such as Sulfurovum, Desulfocapsa, Lutibacter, and Desulforomonas dominated the ice segments and heterotrophic genera such as Cellulomonas and Conexibacter dominated the sediment layers. Sediment layer cDNA iTag sequences indicated that the taxa carrying the potential for metabolic capacity were mostly the Proteobacteria-affiliated genera Pseudoalteromonas and Vibrio. Representatives of these genera are often identified in Antarctic marine environments such as sea-ice, seawater, and marine sediment and adapted to low temperatures and high salinity. Therefore, the detection of abundant and considerably diverse microbial assemblages in Lake Vida brine, ice and sediment layers indicates that life is likely sustained in isolated deep, icy and dark anoxic environments. This also suggests that if similar conditions are found elsewhere beyond Earth, there is the possibility to find life. The second subject in this dissertation research was to conduct an in-depth assessment of the environmental genomics of the archaeal phylum Thaumarchaeota within Antarctic surface seawaters during the wintertime. Thaumarchaeota (earlier identified as Marine Group I.1a) composes 10-30% of the bacterioplankton during the winter in Antarctic surface seawaters playing a noteworthy role in carbon fixation coupled to ammonia oxidation. By comparative genomic analyses, we found that the Antarctic Group I.1a genome fragments represent a unique low diversity Group I.1a cluster affiliated with a "Ca. Nitrosopumilus" that has not yet been cultivated. Antarctic Group I.1a exhibited highly conserved genes in a rearranged genomic structure when compared to the genome of Nitrosopumilus maritimus SCM1indicating a high frequency of recombination (30% of the Antarctic Group I.1a open reading frames). Overall, our results provided insights into the genomic variability of a thaumarchaeal Antarctic assemblage indicating very low diversity that motivates the importance of acquiring the Antarctic strain in pure culture for further analysis of its physiological capacities and evolutionary history

Towards Rapid Label-free Enrichment of Specific Stem Cell Populations for Autologous Cell Therapies

Autologous mesenchymal stem cell (MSC) therapies have huge potential in addressing clinical challenges for otherwise intractable diseases. Label-free, intra-operative separation and enrichment of MSC subpopulations would provide a step change in delivery of such therapies. The long term goal of this research is to use binding proteins to provide a surface with switchable affinity, coupled with microfluidics to selectively bind and subsequently collect released cells. The specific aim of this thesis was to take the first steps towards achieving this goal, by identifying the most suitable binding proteins for cell capture and release in a prototype device and determining the feasibility of cell enrichment from complex clinical samples such as bone marrow aspirate. A prototype device was developed exploiting the cell surface marker CD271 to select for MSCs. Affimer binding proteins and a commercially available antibody were investigated for specific cell capture and release. Specificity for CD271+ cells was demonstrated via flow cytometry using two different cell types. CD271 binding proteins were immobilised to a low-fouling substrate in a microfluidic channel and known mixtures of the two cell populations used to demonstrate specific cell capture. Increased flow rates allowed for bound cells to be released, collected and analysed, providing evidence that cells remained viable and minimally manipulated after enrichment. Clinical samples of bone marrow aspirate were then used in the same way and the results compared to gold standard methods of cell sorting. Results showed that the percentage of CD271+ cells selected from bone marrow mononuclear cell populations using the prototype device was similar to results obtained using established cell sorting methodologies. This work demonstrated that affinity capture via antibody technology, together with a surface designed to provide a controlled release mechanism, offers a high-throughput, minimally manipulative approach to select and enrich MSC populations for therapeutic applications

Development and validation of in silico tools for efficient library design and data analysis in high throughput screening campaigns

My PhD project findings have their major application in the early phase of the drug discovery process, in particular we have developed and validated two computational tools (Molecular Assembles and LiGen) to support the hit finding and the hit to lead phases. I have reported here novel methods to first design chemical libraries optimized for HTS and then profile them for a specific target receptor or enzyme. I also analyzed the generated bio-chemical data in order to obtain robust SARs and to select the most promising hits for the follow up. The described methods support the iterative process of validated hit series optimization up to the identification of a lead. In chapter 3, Ligand generator (LiGen), a de novo tool for structure based virtual screening, is presented. The development of LiGen is a project based on a collaboration among Dompé Farmaceutici SpA, CINECA and the University of Parma. In this multidisciplinary group, the integration of different skills has allowed the development, from scratch, of a virtual screening tool, able to compete in terms of performance with long standing, well-established molecular docking tools such as Glide, Autodock and PLANTS. LiGen, using a novel docking algorithm, is able to perform ligand flexible docking without performing a conformational sampling. LiGen also has other distinctive features with respect to other molecular docking programs: • LiGen uses the inverse pharmacophore derived from the binding site to identify the putative bioactive conformation of the molecules, thus avoiding the evaluation of molecular conformations which do not match the key features of the binding site. • LiGen implemenst a de novo molecule builder based on the accurate definition of chemical rules taking account of building block (reagents) reactivity. • LiGen is natively a multi-platform C++ portable code designed for HPC applications and optimized for the most recent hardware architectures like the Xeon Phi Accelerators. Chapter 3 also reports the further development and optimization of the software starting from the results obtained in the first optimization step performed to validate the software and to derive the default parameters. In chapter 4, the application of LiGen in the discovery and optimization of novel inhibitors of the complement factor 5 receptor (C5aR) is reported. Briefly, the C5a anaphylatoxin acting on its cognate G protein-coupled receptor C5aR is a potent pronociceptive mediator in several models of inflammatory and neuropathic pain. Although there has long been interest in the identification of C5aR inhibitors, their development has been complicated, as is the case with many peptidomimetic drugs, mostly due to the poor drug-like properties of these molecules. Herein, we report the de novo design of a potent and selective C5aR noncompetitive allosteric inhibitor, DF2593A. DF2593A design was guided by the hypothesis that an allosteric site, the “minor pocket”, previously characterized in CXCR1 and CXCR2, could be functionally conserved in the GPCR class.DF2593A potently inhibited C5a-induced migration of human and rodent neutrophils in vitro. Moreover, oral administration of DF2593A effectively reduced mechanical hyperalgesia in several models of acute and chronic inflammatory and neuropathic pain in vivo, without any apparent side effects. Chapter 5 describes another tool: Molecular Assemblies (MA), a novel metrics based on a hierarchical representation of the molecule based on different representations of the scaffold of the molecule and pruning rules. The algorithm used by MA, defining a priori a metrics (a set of rules), creates a representation of the chemical structure through hierarchical decomposition of the scaffold in fragments, in a pathway invariant way (this feature is novel with respect to the other algorithms reported in literature). Such structure decomposition is applied to nine hierarchical representation of the scaffold of the reference molecule, differing for the content of structural information: atom typing and bond order (this feature is novel with respect to the other algorithms reported in literature) The algorithm (metrics) generates a multi-dimensional hierarchical representation of the molecule. This descriptor applied to a library of compounds is able to extract structural (molecule having the same scaffold, wireframe or framework) and sub structural (molecule having the same fragments in common) relations among all the molecules. At least, this method generates relations among molecules based on identities (scaffolds or fragments). Such an approach produces a unique representation of the reference chemical space not biased by the threshold used to define the similarity cut-off between two molecules. This is in contrast to other methods which generate representations based in similarities. MA procedure, retrieving all scaffold representation, fragments and fragmentation’s patterns (according to the predefined rules) from a molecule, creates a molecular descriptor useful for several cheminformatics applications: • Visualization of the chemical space. The scaffold relations (Figure 7) and the fragmentation patterns can be plotted using a network representation. The obtained graphs are useful depictions of the chemical space highlighting the relations that occur among the molecule in a two dimensional space. • Clustering of the chemical space. The relations among the molecules are based on identities. This means that the scaffold representations and their fragments can be used as a hierarchical clustering method. This descriptor produces clusters that are independent from the number and similarity among closest neighbors because belonging to a cluster is a property of the single molecule (Figure 8). This intrinsic feature makes the scaffold based clustering much faster than other methods in producing “stable” clusters in fact, adding and removing molecules increases and decreases the number of clusters while adding or removing relations among the clusters. However these changes do not affect the cluster number and the relation of the other molecules in dataset. • Generate scaffold-based fingerprints. The descriptor can be used as a fingerprint of the molecule and to generate a similarity index able to compare single molecules or also to compare the diversity of two libraries as a whole. Chapter 6 reports an application of MA in the design of a diverse drug-like scaffold based library optimized for HTS campaigns. A well designed, sizeable and properly organized chemical library is a fundamental prerequisite for any HTS project. To build a collection of chemical compounds with high chemical diversity was the aim of the Italian Drug Discovery Network (IDDN) initiative. A structurally diverse collection of about 200,000 chemical molecules was designed and built taking into account practical aspects related to experimental HTS procedures. Algorithms and procedures were developed and implemented to address compound filtering, selection, clusterization and plating. Chapter 7 collects concluding remarks and plans for the further development of the tools

The Development and Applications of the HINT Scoring Function: Exploring Colchicine-Site Anticancer Agents and Tautomerism

The overall aim of this work was to apply HINT, an empirical scoring function based on the understanding of hydrophobicity, to analyze and predict the binding affinities and biological activities of colchicine-site anticancer agents. The second, concurrent aim was to improve the scoring function by incorporating tautomerism within the modeling process. Our belief is that proper evaluation of tautomeric forms for small molecules will improve performance of virtual screening. The novel pyrrole-based compounds targeting the colchicine site were docked into the receptor using HINT as a rescoring function. Two distinct binding modes dictated by the size and shape of a subpocket were predicted to differentiate the highly active compounds from the weak ones. Of the residues predicted to participate in binding for the active binding mode, Cys241β was revealed to form a weak but critical hydrogen bond with the ligand. A larger collection of colchicine-site agents, biologically tested in the same laboratory including our pyrrole-based compounds were subject to 3D quantitative structure-activity relationship (QSAR) study. Using results on docking the pyrrole compounds as a guide, relative binding poses and QSAR models were built to facilitate ligand design and optimization. A new 3D modeling approach was introduced to visually highlight the unique features of highly active compounds and the commonality of all compounds in the dataset using HINT maps and successfully tested on the colchicine-site agents. These results will provide valuable guidance in the future design and development of new colchicine-site agents. To incorporate tautomerism within HINT, we proposed and developed two workflow approaches: a general search tool using a simple and intuitive algorithm analyzing hydrogen shift patterns to identify and enumerate tautomeric structures, and a database that contains commonly observed tautomeric structures. The first approach was designed for small-scale docking studies and the second approach was designed for large-scale virtual screening. The tautomer module in HINT will give more accurate modeling results when the compound encountered is able to tautomerize