Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space

Abstract

The use of modern data science has recently emerged as a promising new path to tackling the complex challenges involved in the creation of next-generation chemistry and materials. However, despite the appeal of this potentially transformative development, the chemistry community has yet to incorporate it as a central tool in every-day work. Our research program is designed to enable and advance this emerging research approach. It is centred around the creation of a software ecosystem that brings together physics-based modelling, high-throughput in silico screening and data analytics (i.e. the use of machine learning and informatics for the validation, mining and modelling of chemical data). This cyberinfrastructure is devised to offer a comprehensive set of data science techniques and tools as well as a general-purpose scope to make it as versatile and widely applicable as possible. It also emphasises user-friendliness to make it accessible to the community at large. It thus provides the means for the large-scale exploration of chemical space and for a better understanding of the hidden mechanisms that determine the properties of complex chemical systems. Such insights can dramatically accelerate, streamline and ultimately transform the way chemical research is conducted. Aside from serving as a production-level tool, our cyberinfrastructure is also designed to facilitate and assess methodological innovation. Both the software and method development work are driven by concrete molecular design problems, which also allow us to assess the efficacy of the overall cyberinfrastructure.     

One Dog,but Which Dog? How Researchers Guide Participants to Select Dogs in Surveys of Human–Dog Relationships

Surveys and questionnaires are regularly used in studies of human–animal relationships. However, little attention has been given to understanding how survey participants are provided with instructions for the selection of a single animal within a multi-pet household, let alone the implications for reporting and interpreting data. We reviewed the instructions for the selection of an individual animal in studies addressing emotional or psychological attachment between people and dogs. By searching multidisciplinary journals from the year 2000 onwards, we identified a total of 128 papers, of which 63 met the inclusion criteria. Where selection criteria/instructions were not clear, authors were contacted. One in five studies (21%, or n = 13) did not report their instructions. When provided, instructions varied considerably. The most commonly provided direction was “favorite/closest relationship” (n = 12, or 19%). The remainder (n = 38, or 60%) were spread across eight different categories. Around half of the studies used a validated questionnaire that already contained an instruction, though a similar proportion of studies implemented author-designed instruments. Overall, the common absence and inconsistency of instructions for individual dog selection is taken to imply that there is no standard expectation or approach for instructions to be reported in studies of human relationships with dogs, or human–animal relationships more generally. We recommend further research on the implication of selection methods to ensure that instructions can be matched with specific research aims.     

Structure-based design and synthesis of macrocyclic human rhinovirus 3C protease inhibitors

The design and synthesis of macrocyclic inhibitors of human rhinovirus 3C protease is described. A macrocyclic linkage of the P1 and P3 residues, and the subsequent structure-based optimization of the macrocycle conformation and size led to the identification of a potent biochemical inhibitor 10 with sub-micromolar antiviral activity.     

Design,synthesis, and biological evaluation of novel ubiquitin-activating enzyme inhibitors

Ubiquitin-activating enzyme (E1), which catalyzes the activation of ubiquitin in the initial step of the ubiquitination cascade, is a potential therapeutic target in multiple myeloma and breast cancer treatment. However, only a few E1 inhibitors have been reported to date. Moreover, there has been little medicinal chemistry research on the three-dimensional structure of E1. Therefore, in the present study, we attempted to identify novel E1 inhibitors using structure-based drug design. Following the rational design, synthesis, and in vitro biological evaluation of several such compounds, we identified a reversible E1 inhibitor (4b). Compound 4b increased p53 levels in MCF-7 breast cancer cells and inhibited their growth. These findings suggest that reversible E1 inhibitors are potential anticancer agents.     

ROCK inhibitors 2. Improving potency,selectivity and solubility through the application of rationally designed solubilizing groups

Solubilizing groups have been frequently appended to kinase inhibitor drug molecules when solubility is insufficient for pharmaceutical development. Such groups are usually located at substitution sites that have minimal impact on target activity. In this report we describe the incorporation of solubilizing groups in a class of Rho kinase (ROCK) inhibitors that not only confer improved solubility, but also enhance target potency and selectivity against a closely related kinase, PKA.     

Dual blockade of VEGFR1 and VEGFR2 by a novel peptide abrogates VEGF-driven angiogenesis,tumor growth,and metastasis through PI3K/AKT and MAPK/ERK1/2 pathway

Background

Neutralization of vascular endothelial growth factor receptor 1 (VEGFR1) and/or VEGFR2 is a widely used means of inhibiting tumor angiogenesis.

Discovery of potent polyphosphate kinase 1 (PPK1) inhibitors using structure‐based exploration of PPK1Pharmacophoric space coupled with docking analyses

Inorganic polyphosphate (polyP) is present in all living forms of life. Studied mainly in prokaryotes, polyP and its associated enzymes are vital in diverse metabolic activities, in some structural functions, and most importantly in stress responses. Bacterial species, including many pathogens, encode a homolog of a major polyP synthesis enzyme, Poly Phosphate Kinase (PPK) with 2 different genes coding for PPK1 and PPK2. Genetic deletion of the ppk1 gene leads to reduced polyP levels and the consequent loss of virulence and stress adaptation responses. This far, no PPK1 homolog has been identified in higher‐order eukaryotes, and, therefore, PPK1 represents a novel target for chemotherapy. The aim of the current study is to investigate PPK1 from Escherichia coli with comprehensive understanding of the enzyme's structure and binding sites, which were used to design pharmacophores and screen a library of compounds for potential discovery of selective PPK1 inhibitors. Verification of the resultant inhibitors activities was conducted using a combination of mutagenic and chemical biological approaches. The metabolic phenotypic maps of the wild type E. coli (WT) and ppk1 knockout mutant were generated and compared with the metabolic map of the chemically inhibited WT. In addition, biofilm formation ability was measured in WT, ppk1 knockout mutant, and the chemically inhibited WT. The results demonstrated that chemical inhibition of PPK1, with the designed inhibitors, was equivalent to gene deletion in altering specific metabolic pathways, changing the metabolic fingerprint, and suppressing the ability of E. coli to form a biofilm.     

Integration of molecular dynamics simulation and hotspot residues grafting for de novo scFv design against Salmonella Typhi TolC protein

With the development of de novo binders for protein targets from non‐related scaffolds, many possibilities for therapeutics and diagnostics have been created. In this study, we described the use of de novo design approach to create single‐chain fragment variable (scFv) for Salmonella enterica subspecies enterica serovar Typhi TolC protein. Typhoid fever is a global health concern in developing and underdeveloped countries. Rapid typhoid diagnostics will improve disease management and therapy. In this work, molecular dynamics simulation was first performed on a homology model of TolC protein in POPE membrane bilayer to obtain the central structure that was subsequently used as the target for scFv design. Potential hotspot residues capable of anchoring the binders to the target were identified by docking “disembodied” amino acid residues against TolC surface. Next, scFv scaffolds were selected from Protein Data Bank to harbor the computed hotspot residues. The hotspot residues were then incorporated into the scFv scaffold complementarity determining regions. The designs recapitulated binding energy, shape complementarity, and interface surface area of natural protein‐antibody interfaces. This approach has yielded 5 designs with high binding affinity against TolC that may be beneficial for the future development of antigen‐based detection agents for typhoid diagnostics.     

Redesign of LAOBP to bind novel l‐amino acid ligands

Computational protein design is still a challenge for advancing structure‐function relationships. While recent advances in this field are promising, more information for genuine predictions is needed. Here, we discuss different approaches applied to install novel glutamine (Gln) binding into the Lysine/Arginine/Ornithine binding protein (LAOBP) from Salmonella typhimurium. We studied the ligand binding behavior of two mutants: a binding pocket grafting design based on a structural superposition of LAOBP to the Gln binding protein QBP from Escherichia coli and a design based on statistical coupled positions. The latter showed the ability to bind Gln even though the protein was not very stable. Comparison of both approaches highlighted a nonconservative shared point mutation between LAOBP_graft and LAOBP_sca. This context dependent L117K mutation in LAOBP turned out to be sufficient for introducing Gln binding, as confirmed by different experimental techniques. Moreover, the crystal structure of LAOBP_L117K in complex with its ligand is reported.