CurlySMILES: a chemical language to customize and annotate encodings of molecular and nanodevice structures

CurlySMILES is a chemical line notation which extends SMILES with annotations for storage, retrieval and modeling of interlinked, coordinated, assembled and adsorbed molecules in supramolecular structures and nanodevices. Annotations are enclosed in curly braces and anchored to an atomic node or at the end of the molecular graph depending on the annotation type. CurlySMILES includes predefined annotations for stereogenicity, electron delocalization charges, extra-molecular interactions and connectivity, surface attachment, solutions, and crystal structures and allows extensions for domain-specific annotations. CurlySMILES provides a shorthand format to encode molecules with repetitive substructural parts or motifs such as monomer units in macromolecules and amino acids in peptide chains. CurlySMILES further accommodates special formats for non-molecular materials that are commonly denoted by composition of atoms or substructures rather than complete atom connectivity

Evolutionary Multi-Objective Design of SARS-CoV-2 Protease Inhibitor Candidates

Computational drug design based on artificial intelligence is an emerging research area. At the time of writing this paper, the world suffers from an outbreak of the coronavirus SARS-CoV-2. A promising way to stop the virus replication is via protease inhibition. We propose an evolutionary multi-objective algorithm (EMOA) to design potential protease inhibitors for SARS-CoV-2's main protease. Based on the SELFIES representation the EMOA maximizes the binding of candidate ligands to the protein using the docking tool QuickVina 2, while at the same time taking into account further objectives like drug-likeliness or the fulfillment of filter constraints. The experimental part analyzes the evolutionary process and discusses the inhibitor candidates.Comment: 15 pages, 7 figures, submitted to PPSN 202

Modular Chemical Descriptor Language (MCDL): Stereochemical modules

<p>Abstract</p> <p>Background</p> <p>In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures.</p> <p>Results</p> <p>In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDL processing module software packages.</p> <p>Conclusions</p> <p>Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.</p

Hole transfer equilibrium in rigidly linked bichromophoric molecules

Two bichromophoric molecules consisting of anthracene and diphenylpolyene moieties linked by two fused norbornyl bridges undergo photoionization upon ultraviolet (UV) pulsed laser irradiation. The simultaneous observation of the cation radicals of both anthracene and polyene groups points to a rapid (nanosecond or faster) intramolecular hole transfer equilibrium between the two chromophores. The existence of an equilibrium is supported by the results of one- and two-laser transient absorption and electrochemical experiments. Equilibrium constants (293 K) were determined by both transient absorption and cyclic voltammetry measurements and were independent of the method used within experimental error. For A-sp-VB, which contains anthracene and vinyldiphenylbutadiene chromophores, Keq = 4.0 ? 2 (transient absorption) and 3.2 ? 2 (electrochemical), favoring the anthracene cation radical. For A-sp-VS, containing anthracene and vinylstilbene groups, Keq = 70 ? 30 (transient absorption) and 105 ? 50 (electrochemical), favoring the anthracene cation radical.Peer reviewed: YesNRC publication: Ye

Screensaver: an open source lab information management system (LIMS) for high throughput screening facilities

<p>Abstract</p> <p>Background</p> <p>Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups.</p> <p>Results</p> <p>We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects.</p> <p>Conclusions</p> <p>The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities.</p

Visual Network Analysis of Dynamic Metabolic Pathways

Abstract. We extend our previous work on the exploration of static metabolic networks to evolving, and therefore dynamic, pathways. We apply our visualization software to data from a simulation of early metabolism. Thereby, we show that our technique allows us to test and argue for or against different scenarios for the evolution of metabolic pathways. This supports a profound and efficient analysis of the structure and properties of the generated metabolic networks and its underlying components, while giving the user a vivid impression of the dynamics of the system. The analysis process is inspired by Ben Shneiderman’s mantra of information visualization. For the overview, user-defined diagrams give insight into topological changes of the graph as well as changes in the attribute set associated with the participating enzymes, substances and reactions. This way, “interesting features” in time as well as in space can be recognized. A linked view implementation enables the navigation into more detailed layers of perspective for in-depth analysis of individual network configuration

Interpreting linear support vector machine models with heat map molecule coloring

<p>Abstract</p> <p>Background</p> <p>Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity.</p> <p>Results</p> <p>We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor.</p> <p>Conclusions</p> <p>In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor.</p

Consumer satisfaction with primary care provider choice and associated trust

BACKGROUND: Development of managed care, characterized by limited provider choice, is believed to undermine trust. Provider choice has been identified as strongly associated with physician trust. Stakeholders in a competitive healthcare market have competing agendas related to choice. The purpose of this study is to analyze variables associated with consumer's satisfaction that they have enough choice when selecting their primary care provider (PCP), and to analyze the importance of these variables on provider trust. METHODS: A 1999 randomized national cross-sectional telephone survey conducted of United States residential households, who had a telephone, had seen a medical professional at least twice in the past two years, and aged ≥ 20 years was selected for secondary data analyses. Among 1,117 households interviewed, 564 were selected as the final sample. Subjects responded to a core set of questions related to provider trust, and a subset of questions related to trust in the insurer. A previously developed conceptual framework was adopted. Linear and logistic regressions were performed based on this framework. RESULTS: Results affirmed 'satisfaction with amount of PCP choice' was significantly (p < .001) associated with provider trust. 'PCP's care being extremely effective' was strongly associated with 'satisfaction with amount of PCP choice' and 'provider trust'. Having sought a second opinion(s) was associated with lower trust. 'Spoke to the PCP outside the medical office,' 'satisfaction with the insurer' and 'insurer charges less if PCP within network' were all variables associated with 'satisfaction with amount of PCP choice' (all p < .05). CONCLUSION: This study confirmed the association of 'satisfaction with amount of PCP choice' with provider trust. Results affirmed 'enough PCP choice' was a strong predictor of provider trust. 'Second opinion on PCP' may indicate distrust in the provider. Data such as 'trust in providers in general' and 'the role of provider performance information' in choice, though import in PCP choice, were not available for analysis and should be explored in future studies. Results have implications for rethinking the relationships among consumer choice, consumer behaviors in making trade-offs in PCP choice, and the role of healthcare experiences in 'satisfaction with amount of PCP choice' or 'provider trust.