Sulev Sild's research while affiliated with University of Tartu and other places
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Publications (53)
Intrinsic aqueous solubility is a foundational property for understanding the chemical, technological, pharmaceutical, and environmental behavior of drug substances. Despite years of solubility research, molecular structure-based prediction of the intrinsic aqueous solubility of drug substances is still under active investigation. This paper descri...
Ionic liquids (ILs) are known for their unique characteristics as solvents and electrolytes. Therefore, new ILs are being developed and adapted as innovative chemical environments for different applications in which their properties need to be understood on a molecular level. Computational data-driven methods provide means for understanding of prop...
Ionic liquids (ILs) have unique properties as solvents and electrolytes, which need to be studied using innovative machine learning (ML) approaches and which allow the identification of a chemical environment that can be adapted to different applications. The gas-ionic liquid partition coefficients of organic compounds is one such application-orien...
Androgens and androgen receptor regulate a variety of biological effects in the human body. The impaired functioning of androgen receptor may have different adverse health effects from cancer to infertility. Therefore, it is important to determine whether new chemicals have any binding activity and act as androgen agonists or antagonists before com...
Background:
Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need i...
The rate at which toxicological data is generated is continually becoming more rapid and the volume of data generated is growing dramatically. This is due in part to advances in software solutions and cheminformatics approaches which increase the availability of open data from chemical, biological and toxicological and high throughput screening res...
Permeability is used to describe and evaluate the absorption of drug substances in the human gastrointestinal tract (GIT). Permeability is largely dependent on fluctuating pH that causes the ionization of drug substances and also influences regional absorption in the GIT. Therefore, classification models that characterize permeability at wide range...
BACKGROUND : Quantitative and qualitative structure–activity relationships (QSARs) have been used to understand chemical behavior for almost a century. The main source of QSAR models is the scientific literature, but the open question is how well these models are documented.
OBJECTIVES : The main aim of this study was to critically analyze the publ...
Structure-activity relationship models have been used to gain insight into chemical and physical processes in biomedicine, toxicology, biotechnology, etc. for almost a century. They have been recognized as valuable tools in decision support workflows for qualitative and quantitative predictions. The main obstacle preventing broader adoption of quan...
A virtual screening to find novel inhibitors for HIV protease was performed on the ZINC database.1 A critical part in virtual screening and associated techniques is preliminary database filtering and size reduction and for that purpose a novel feature matrix matching procedure was used. The reduction of ∼14 million available ligands to a subset of...
In environmental risk assessment, the bio-concentration factor (BCF) is a widely used parameter in the estimation of the bio-accumulation potential of chemicals. BCF data often have an uneven distribution of classes (bio-accumulative vs. non-bio-accumulative), which could severely bias the classification results towards the prevailing class. The pr...
Background
Research efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure–Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvi...
Quantitative structure-activity relationships (QSARs) are broadly classified as global or local, depending on their molecular constitution. Global models use large and diverse training sets covering a wide range of chemical space. Local models focus on smaller structurally or chemically similar subsets that are conventionally selected by human expe...
New hits against HIV-1 wild-type and Y181C drug-resistant reverse transcriptases were predicted taking into account the possibility of some of the known metabolism interactions. In silico hits against a set of antitargets (i.e., proteins or nucleic acids that are off-targets from the desired pharmaceutical target objective) are used to predict a si...
Pseudouridine [Ψ] is a frequent base modification in the ribosomal RNA [rRNA] and may be involved in the modulation of the conformational flexibility of rRNA helix-loop structures during protein synthesis. Helix 69 of 23S rRNA contains pseudouridines at the positions 1911, 1915 and 1917 which are formed by the helix 69-specific synthase RluD. The g...
Today, many scientific disciplines heavily rely on computer systems for in-silico experimentation or data management and analysis. The employed computer hard- and software is heterogeneous and complies to different standards, interfaces and protocols for interoperation. Grid middleware systems like UNICORE 6 try to hide some of the complexity of th...
In Silico methods to predict toxicity have become increasingly important recently, particularly in light of European legislation such as REACH and the Cosmetics Regulation. They are also being used extensively worldwide e.g. in the USA, Canada, Japan and Australia. In assessing the risk that a chemical may pose to human health or to the environment...
The in silico modelling of bio-concentration factor (BCF) is of considerable interest in environmental sciences, because it is an accepted indicator for the accumulation potential of chemicals in organisms. Numerous QSAR models have been developed for the BCF, and the majority utilize the octanol/water partition coefficient (log P) to account for t...
The relationships between structure and passive permeability in artificial membranes were studied using a structurally diverse data set of 60 compounds. The potential of whole molecule descriptors in the development of QSAR models was explored and the respective five-parameter model is presented for the modeling of permeability. The presented QSAR...
A QSAR analysis was carried out on a dataset of 126 anthraquinone-based cytotoxic compounds. A PCA of the molecular descriptors was used to cluster the dataset into smaller subsets according to their structural features and QSAR models were derived for the selected sets. During the modeling, protonated states of molecules and nonlinear transformati...
Distributed grid technologies are gradually realizing their potential to provide innovative infrastructures for complex scientific and industrial applications in the field of computational chemistry and related application areas. The current paper gives examples of distributed solutions for docking and virtual screening applications in moving the c...
This chapter provides an overview of Grid middleware and applications related to biomedical and life sciences disciplines. Various technologies, including web-based solutions, are presented. One of the solutions, the UNICORE framework, in its recent version implements key grid standards and specifications. The system architecture and capabilities,...
ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
A Quantitative Structure–Activity Relationship (QSAR) analysis was carried out on a dataset of 135 six- and seven-membered cyclic urea-based Human Immunodeficiency Virus Type 1 (HIV-1) protease inhibitors. Using a larger and more diverse dataset than previous studies reported in literature allowed a more comprehensive analysis. A large set of molec...
Intersubunit bridges are important for holding together subunits in the 70S ribosome. Moreover, a number of intersubunit bridges have a role in modulating the activity of the ribosome during translation. Ribosomal intersubunit bridge B2a is formed by the interaction between the conserved 23S rRNA helix-loop 69 (H69) and the top of the 16S rRNA heli...
The binding sites of wild-type avian influenza A H5N1 neuraminidase, as well as those of the Tamiflu (oseltamivir)-resistant H274Y variant, were explored computationally to design inhibitors that target simultaneously several adjacent binding sites of the open conformation of the virus protein. The compounds with the best computed free energies of...
Polarizability is one of the key properties determining the nonlinear optical effects of the new materials. In the current study, a quantitative structure−property relationship approach is used to model the polarizability of polyaromatic hydrocarbons (PAHs) and fullerenes. The model is derived using the data set of 40 PAHs and fullerenes and includ...
ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
During the last years, considerable effort has been devoted to model the toxicity of chemicals to Tetrahymena pyriformis for medium and large sized data sets using various artificial neural network (ANN) techniques. Motivation behind this has been to model highly complex relationships with nonlinear character making it possible to describe wide str...
Solubility of polyaromatic hydrocarbons (PAH) and carbon nanostructures is important both from the technical and environmental points of view. In the present work, two general quantitative structure-property relationship (QSPR) models were developed, describing the solubility of PAH-s and fullerene (C60) in two different condensed media (1-octanol...
Chemomentum, Grid Services based Environment to enable Innovative Research, is an end-user focused approach to exploit Grid computing for diverse application domains. Building on top of UNICORE 6, we are designing and implementing a flexible, user-friendly Grid system focussing on high-performance processing of complex application workflows and man...
The computational estimation of toxicity is time-consuming and therefore needs support for distributed, high-performance and/or
grid computing. The major technology behind the estimation of toxicity is quantitative structure activity relationship modelling.
It is a complex procedure involving data gathering, preparation and analysis. The current pa...
Data mining and knowledge exploration of chemical information is the key step in life science fields, such as drug discovery, property/activity prediction and many others, where the meaningful linking of experimental knowledge and information about chemical structure is necessary. In these fields the applications are often based on quantitative str...
Chemomentum, Grid Services based Environment to enable Innovative Research, is an end-user focused approach to exploit Grid
computing for diverse application domains. Building on top of UNICORE 6, we are designing and implementing a flexible, user-friendly
Grid system focussing on high-performance processing of complex application workflows and man...
The nonlinear QSAR approach using the Chebyshev polynomial expansion and neural networks has been applied for the prediction of genotoxicity of compounds. The mutagenic toxicity of heteroaromatic and aromatic amines, measured by the Ames test, was correlated with the molecular descriptors calculated from the molecular structures using quantum-chemi...
Grid is an emerging infrastructure for distributed computing that provides secure and scalable mechanisms for discovering and accessing remote software and data resources. Applications built on this infrastructure have great potential for addressing and solving large scale chemical, pharmaceutical, and material science problems. The article describ...
Quantitative Structure Activity/Property Relationship (QSAR/QSPR) model development is a complex and time-consuming procedure involving data gathering and preparation. It plays an important role in the drug discovery pipe- line, which still is mostly done manually. The current paper describes the auto- mated workflow support of the OpenMolGRID syst...
Modern approaches to chemistry and pharmacology deal with large-scale molecular design problems. The molecular design is essentially based on data warehousing and data mining. Data warehousing techniques are needed to collect relevant data from distributed and heterogeneous databases. Data mining techniques are used to build predictive quantitative...
Multilinear regression and neural network methods have been used to develop QSPR models for the prediction of the dielectric constant (epsilon) and Kirkwood function (epsilon - 1)/(2epsilon + 1) of organic liquids. Both methods can provide acceptable models for the prediction of these properties. The QSPR models developed from the training set of 1...
The results of the quantitative structure -property relationship (QSPR) analysis of 45 different solvent scales and 350 solvents using the CODESSA program are presented. The QSPR models for each of the scales are constructed using only theoretical descriptors. The high quality of the models (32 of the 45 give R2 > 0.90, only two have R2 < 0.82) ena...
The selection of the most relevant variable is a frequent problem in the analysis of chemical data, especially now considering the large amounts of data created by the increased computer power and analytical resolution. A novel procedure for variable selection based on multiregression (MR) analysis is developed and applied to the quantitative struc...
The selection of the most relevant variable is a frequent problem in the analysis of chemical data, especially now considering the large amounts of data created by the increased computer power and analytical resolution. A novel procedure for variable selection based on multiregression (MR) analysis is developed and applied to the quantitative struc...
A general QSPR model (R2 ) 0.940, s ) 0.018) was developed for the prediction of the refractive index for a diverse set of amorphous homopolymers with the CODESSA program. The five descriptors, involved in the model, are calculated from the structure of the repeating unit of the polymer. The average prediction error by this model is 0.9%. can be ea...
A general five parameter quantitative structure-property relationship (QSPR) model (R2 ) 0.945, s ) 0.0155) is described for the refractive index of a structurally diverse data set of 125 organic compounds. The model, developed with the CODESSA program, involves quantum chemical, topological, and constitutional descriptors.
The vapor pressures and the aqueous solubilities of 411 compounds with a large structural diversity were investigated using a quantitative structure-property relationship (QSPR) approach. A five-descriptor equation with the squared correlation coefficient (R-2) Of 0.949 for vapor pressure and a six-descriptor equation with R-2 of 0.879 for aqueous...
Recent claims that linear relationships exist between energetic, geometric, and magnetic criteria of aromaticity are shown to be invalid for any representative set of heteroaromatics in which the number of heteroatoms varies.
A new quantitative structure-property relationship (QSPR) five-parameter correlation (R-2 = 0.946) of molar glass transition temperatures (T-g/M) for a diverse set of 88 polymers is developed with the Comprehensive Descriptors for Structural and Statistical Analysis (CODESSA) program. The descriptors are all calculated directly from the molecular s...
Citations
... The pursuit of accurate prediction of solubility of drugs from molecular structure is still evolving and continues to be challenging [1][2][3][4][5][6][7]. It had been proposed that shortfalls have been due to the lack of high-quality solubility data from the chemical space of drugs. ...
... SVR algorithm formulates function approximation problem as an optimization problem, while minimizing the distance between the predicted and the desired outputs [20][21][22]. Because our problem was not linearly separable in input space, a kernel was used to transform the data to a higher-dimensional space, referred to as kernel space, where data will be linearly separable. ...
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... Further, as both the ion-pair combination and the diverse space of solute features need to be explored, the computational cost is orders-of-magnitude costlier than the bulk case, which makes it practically intractable in large-scaling applications. Unfortunately, although there are some parametric models developed for molecular solvation in specific ILs, 28,29 currently there is no established predictive model for solvation and partition thermodynamics with a wide coverage of popular ILs species. ...
... However, CoMFA technique is very less reproducible and complicated as it requires conformational analysis and alignment of compounds. Further, Piir et al. (Piir et al., 2021) did only qualitative predictions. Roy et al. (Banerjee et al., 2022a) developed 2D-QSAR, Quantitative Read-Across and q-RASAR based models. ...
... Multiorganisation collaborations have also evaluated multiple models for a specific effect e.g. ER (Mansouri et al. 2016) and AR (Mansouri et al. 2020) effects. Therefore, we have conducted a side-by-side comparison of multiple different in silico models covering three pathways in ED, namely ER, AR and aromatase inhibition and compared these with Tox-Cast-derived final calls, as well as with results from in vitro assays. ...
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... The MLR, SVR and GPR models and related data can be made available in various data formats [120]. To follow the best practices of QSAR model reporting [121], the models with data are stored at the QsarDB repository [122] in QSAR Data Bank format [123]. ...
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... LogD is a suitable descriptor for the lipophilicity of ionizable drugs since it considers the pH dependence of a molecule in an aqueous solution [24]. The predicted LogD 7.4 of a compound is given as the logarithm of the molar concentration (Log mol/L). ...
... Due to its wide spectrum of utilities, the OECD countries have now already established principles for QSAR modeling consisting of five rules: defined endpoint, unambiguous algorithms, defined applicability domain, modeling validation, and mechanistic interpretation to standardize the application of QSAR/QSPR modeling. This involves all steps of modeling process: data collection, data preprocessing, data splitting, machine learning modeling process, validation of the model, and mechanistic interpretation of feature importance (Fjodorova et al., 2008;Piir et al., 2018;Tropsha, 2010). ...
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... There has been number of different grid infrastructures used. The solution built using UNICORE middleware [8] is an example of the most successful one [9]. ...
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... IC0 is calculated from the Shannon's entropy as −∑ i p i log 2 p i , where the p i is the probability of randomly selecting an atom of a specific type i in the molecule. 36,37 This descriptor characterizes the molecular complexity as the average amount of information per atom type. IC0 is included only logP e_highest and logP o models, which indicates that this descriptor is significant to describe permeability properties for uncharged compounds. ...
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