Serli Önlü

Bio: Serli Önlü is an academic researcher from Boğaziçi University. The author has contributed to research in topics: Applicability domain & Ecotoxicology. The author has an hindex of 6, co-authored 8 publications receiving 67 citations. Previous affiliations of Serli Önlü include University of Tampere & Henkel.

An integrated quantitative structure and mechanism of action-activity relationship model of human serum albumin binding.

Abstract: Traditional quantitative structure-activity relationship models usually neglect the molecular alterations happening in the exposed systems (the mechanism of action, MOA), that mediate between structural properties of compounds and phenotypic effects of an exposure. Here, we propose a computational strategy that integrates molecular descriptors and MOA information to better explain the mechanisms underlying biological endpoints of interest. By applying our methodology, we obtained a statistically robust and validated model to predict the binding affinity to human serum albumin. Our model is also able to provide new venues for the interpretation of the chemical-biological interactions. Our observations suggest that integrated quantitative models of structural and MOA-activity relationships are promising complementary tools in the arsenal of strategies aiming at developing new safe- and useful-by-design compounds.

MaNGA: a novel multi-niche multi-objective genetic algorithm for QSAR modelling

Abstract: SUMMARY Quantitative structure-activity relationship (QSAR) modelling is currently used in multiple fields to relate structural properties of compounds to their biological activities. This technique is also used for drug design purposes with the aim of predicting parameters that determine drug behaviour. To this end, a sophisticated process, involving various analytical steps concatenated in series, is employed to identify and fine-tune the optimal set of predictors from a large dataset of molecular descriptors (MDs). The search of the optimal model requires to optimize multiple objectives at the same time, as the aim is to obtain the minimal set of features that maximizes the goodness of fit and the applicability domain (AD). Hence, a multi-objective optimization strategy, improving multiple parameters in parallel, can be applied. Here we propose a new multi-niche multi-objective genetic algorithm that simultaneously enables stable feature selection as well as obtaining robust and validated regression models with maximized AD. We benchmarked our method on two simulated datasets. Moreover, we analyzed an aquatic acute toxicity dataset and compared the performances of single- and multi-objective fitness functions on different regression models. Our results show that our multi-objective algorithm is a valid alternative to classical QSAR modelling strategy, for continuous response values, since it automatically finds the model with the best compromise between statistical robustness, predictive performance, widest AD, and the smallest number of MDs. AVAILABILITY AND IMPLEMENTATION The python implementation of MaNGA is available at https://github.com/Greco-Lab/MaNGA. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

An in silico algal toxicity model with a wide applicability potential for industrial chemicals and pharmaceuticals.

Abstract: In this study, we modeled the 72 h algal toxicity data of hundreds of chemicals with a different mode of action (MOA) as a function of chemical structures. We developed MOA-based local quantitative structure-toxicity relationship (QSTR) models for non-polar and polar narcotics as well as a global QSTR model with a wide applicability potential for industrial chemicals and pharmaceuticals. We rigorously evaluated the generated models, meeting the OECD principles of robustness, validity and transparency. The proposed global model had a broad structural coverage for the toxicity prediction of diverse chemicals (some of which are high production volume chemicals) with no experimental toxicity data. Our global model is potentially useful for endpoint predictions, the evaluation of algal toxicity screening and the prioritization of chemicals, as well as for the decision of further testing and the development of risk management measures in a scientific and regulatory frame. This article is protected by copyright. All rights reserved

Impact of geometry optimization methods on QSAR modelling: A case study for predicting human serum albumin binding affinity

Abstract: Quantitative structure-activity relationship (QSAR) modelling is a major tool employed in the prediction of various endpoints. However, current QSAR literature is missing a full understanding of the impact of quantum chemical calculation methods on the estimation of molecular descriptors and model performance. Here, we provide a comprehensive analysis of the quantitative effects of different geometry optimization methods (semi-empirical, ab initio Hartee-Fock and density functional theory) on the molecular descriptors. Using experimental binding affinity to human serum albumin (HSA) data, we comparatively investigated the influence of employing descriptors derived from three calculation methods on the QSAR models. We propose a 4-descriptor QSAR model in line with the OECD validation principles for the prediction of drug binding affinity to HSA (log KHSA) as a potential tool for drug development. We also confirm the prediction capability of the proposed model on a heterogeneous external set of chemicals. Furthermore, we recommend an activity-independent rational approach for the selection of geometry optimization method for an improved QSAR model development.

Zen and the Art of Motorcycle Maintenance: An Inquiry into Values

Abstract: ZEN AND THE ART OF MOTORCYCLE MAINTENANCE: An Inquiry into Values, Robert M. Pirsig, HarperCollins Publishers, New York 1974, reprint 2005, 430 pages, $13.95. [ILLUSTRATION OMITTED] Robert Pirsig's Zen and the Art of Motorcycle Maintenance (ZMM) metaphorically outlines the intellectual journey that the War Machine as an institution needs to take in order to reform itself. The perfect place for this reform to begin is in the military's first operational war fighting school, the Army's School of Advanced Military Studies (SAMS). Students at SAMS are reading ZMM in the true spirit of the school, the spirit of intellectual reform. Brigadier General Huba Wass de Czege started SAMS in the early 1980s when he realized that the Army as an institution could not reform itself from the inside, from the topdown. SAMS students learn to think for themselves, freeing themselves from the doctrinal Procrustean bed of black-and-white thinking. ZMM can help us challenge our unconscious schemata of categorical thinking that force us into seeing the world in functional hierarchies made up of block-and-line charts and examine our unconscious conflation of what's in our minds with what's in the world--the reification of our mental models, theories, and myths. ZMM is a timeless classic accessible to anyone courageous enough to challenge his or her own convictions. The understanding gained is not about good old-fashioned heroic, warrior leadership; it is not about decision-making; it is not about problem-solving. It is about critical reasoning. ZMM will not leave the reflective person unaffected. Introduction by LTC Timothy Challans, U.S. Army Retired, Ph.D. Zen and the Art of Motorcycle Maintenance is a bizarre title for a serious piece of literature, yet the title could not be more fitting. The philosophical quandaries in which the narrator engages proffer the reader an opportunity to expand upon traditionally held Western thoughts and values. The storyline is not typical of military readings, but unfortunately neither is the subject of critical thinking, which this book is all about. The title conjures images of Buddhist monks in secluded meditation, but also draws upon imagery of motorcycle maintenance to attract an audience with a proclivity for Western thinking into "an inquiry into values" and serious dialogue on logical reasoning and intuitive judgments about "quality." While taking a cursory, but grounding, tour through 2,500 years of philosophical evolution, the book challenges the reader to consider the value of self-reflection in order to increase the reader's capacity for critical thinking. It is a philosophically engaging modern epic well worth reading. It is not a manual for fixing motorcycles, nor will it have you sitting cross-legged in trancelike meditation, but it will make you scratch your head, challenge the way you think, and make you rethink the way you live. Robert Pirsig uses a father-son motorcycle trip across the northern region and west coast of the U.S. as the backdrop upon which he paints a candid picture of a well-educated, middle-aged man--presumably the author himself--struggling with his sanity. The narrator, previously subjected to electroshock therapy that left mental voids, is physically retracing his past and exploring the philosophical debates and discovery that he was previously obsessed with and which left him committed to an asylum. It is a captivating story filled with imagery to which the reader can easily relate, but the true power of the work is found in Pirsig's ability to use the story to pull the reader through a lesson on early Western philosophy while comparing it to aspects of Eastern philosophy. The narrator navigates through early Greek philosophical developments while drifting through periods of deep internal reflection, contemplating the meaning of artifacts that remain and memories that surface from his life before therapy. …

Grouping of nanomaterials to read-across hazard endpoints: a review

Abstract: The use of non-testing strategies like read-across in the hazard assessment of chemicals and nanomaterials (NMs) is deemed essential to perform the safety assessment of all NMs in due time and at lower costs The identification of physicochemical (PC) properties affecting the hazard potential of NMs is crucial, as it could enable to predict impacts from similar NMs and outcomes of similar assays, reducing the need for experimental (and in particular animal) testing This manuscript presents a review of approaches and available case studies on the grouping of NMs to read-across hazard endpoints We include in this review grouping frameworks aimed at identifying hazard classes depending on PC properties, hazard classification modules in control banding (CB) approaches, and computational methods that can be used for grouping for read-across The existing frameworks and case studies are systematically reported Relevant nanospecific PC properties taken into account in the reviewed frameworks to support grouping are shape and surface properties (surface chemistry or reactivity) and hazard classes are identified on the basis of biopersistence, morphology, reactivity, and solubility

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Abstract: Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.

Metal and metal-oxide nanozymes: bioenzymatic characteristics, catalytic mechanism, and eco-environmental applications.

Abstract: Phenolic contaminants (R-OH) are a category of highly toxic organic compounds that are widespread in aquatic ecosystems and can induce carcinogenic risk to wildlife and humans; natural enzymes as green catalysts are capable of step-polymerizing these compounds to produce diverse macromolecular self-coupling products via radical-mediated C-C and C-O-C bonding at either the ortho- or para-carbon position, thereby evading the bioavailability and ecotoxicity of these compounds. Intriguingly, certain artificial metal and metal-oxide nanomaterials are known as nanozymes. They not only possess the unique properties of nanomaterials but also display intrinsic enzyme-mimicking activities. These artificial nanozymes are expected to surmount the shortcomings, such as low stability, easy inactivation, difficult recycling, and high cost, of natural enzymes, thus contributing to eco-environmental restoration. This review highlights the available studies on the enzymatic characteristics and catalytic mechanisms of natural enzymes and artificial metal and metal-oxide nanozymes in the removal and transformation of R-OH. These advances will provide key research directions beneficial to the multifunctional applications of artificial nanozymes in aquatic ecosystems.