HexServer (http://hexserver.loria.fr/) is the first Fourier transform (FFT)-based protein docking server to be powered by graphics processors. Using two processors simultaneously, a typical 6D run takes ∼15 s, which up orders of magnitude faster than conventional FFT-based approaches using comparable resolution and scoring functions. The requires structures in PDB format uploaded, it produces ranked list 1000 predictions. Knowledge one or both binding sites may used focus shorten calculation...

Abstract Motivation: Modelling protein–protein interactions (PPIs) is an increasingly important aspect of structural bioinformatics. However, predicting PPIs using in silico docking techniques computationally very expensive. Developing fast protein tools will be useful for studying large-scale PPI networks, and could contribute to the rational design new drugs. Results: The Hex spherical polar Fourier algorithm has been implemented on Nvidia graphics processor units (GPUs). On a GTX 285 GPU,...

Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate variety functions. Knowing the tertiary structure protein complex is therefore essential for understanding interaction mechanism. However, experimental techniques to solve often found be difficult. To this end, computational protein-protein docking approaches can provide useful alternative address issue. Prediction conformations relies on methods that effectively capture shape...

In recent years, many virtual screening (VS) tools have been developed that employ different molecular representations and speed accuracy characteristics. this paper, we compare ten popular ligand-based VS using the publicly available Directory of Useful Decoys (DUD) data set comprising over 100 000 compounds distributed across 40 protein targets. The DUD was initially to evaluate docking algorithms, but our results from an operational correlation analysis show it is also well suited for...

Abstract Motivation The absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs plays a key role in determining which among the potential candidates are to be prioritized. In silico approaches based on machine learning methods becoming increasing popular, but nonetheless limited by availability data. With view making both data models available scientific community, we have developed FPADMET is repository molecular fingerprint-based predictive for ADMET properties....

Significance The dissociation of water is arguably the most fundamental chemical reaction occurring in aqueous phase. Despite that splitting a molecule very seldom occurs, major importance many areas chemistry and biology. Direct experimental probing event still impossible also simulating via accurate computer simulations challenging. Here, we achieved latter specialized rare-event algorithms estimating rates agreement with indirect measurements. Even more interestingly, by rigorous analysis...

Abstract Background Dye-sensitized solar cells (DSSCs) have garnered a lot of attention in recent years. The energy to power conversion efficiency DSSC is influenced by various components the cell such as dye, electrolyte, electrodes and additives among others leading varying experimental configurations. A large number metal-based metal-free dye sensitizers now been reported tools using data indicate new directions for design development are on rise. Description DSSCDB, first its kind...

Abstract Summary: We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by vector 3D Zernike descriptors, times for query against the entire PDB take, an average, only couple seconds. The web interface has been be as interactive possible with displays showing animated rotations, CATH codes structural alignments using CE program. In addition,...

Abstract Modeling conformational changes in protein docking calculations is challenging. To make the tractable, most current algorithms typically treat proteins as rigid bodies and use soft scoring functions that implicitly accommodate some degree of flexibility. Alternatively, ensembles structures generated from molecular dynamics (MD) may be cross‐docked. However, such combinatorial approaches can produce many thousands or even millions poses, require fast sensitive to distinguish them....

A computational screening strategy applied to 8 million synthetically diverse ionic liquids, demonstrates its value for sustainable solvent design.

The identification of promising drug leads from a large database compounds is an important step in the preliminary stages design. Although shape known to play key role molecular recognition process, its application virtual screening poses significant hurdles both terms encoding scheme and speed.In this study, we have examined efficacy alignment independent three-dimensional Zernike descriptor (3DZD) for fast based similarity searching. Performance approach was compared with several other...

A method for the automated generation of realistic, synthetically accessible transition metal and organometallic complexes is described. Computational tools were designed to generate molecular fragments, preferably harvested from libraries existing, stable compounds, be used as building blocks construction new molecules. These fragments are enriched with information about number type possible connections other stored in library files. When connecting subsequent process, compatibility...

A machine learning strategy is presented for the rapid discovery of new polymeric materials satisfying multiple desirable properties. Of particular interest design high refractive index polymers. Our in silico approach employs a series quantitative structure–property relationship models that facilitate virtual screening polymers based on relevant properties such as index, glass transition and thermal decomposition temperatures, solubility standard solvents. Exploration chemical space carried...

A general-purpose software package, termed DE Novo OPTimization of In/organic Molecules (DENOPTIM), for de novo design and virtual screening functional molecules is described. any element kind, including metastable species transition states, are handled as chemical objects that go beyond valence-rules representations. Synthetic accessibility the generated ensured via detailed control kinds bonds allowed to form in automated molecular building process. DENOPTIM contains a combinatorial...

Abstract Dye adsorption on metal-oxide films often results in small to substantial absorption shifts relative the solution phase, with undesirable consequences for performance of dye-sensitized solar cells and optical sensors. While density functional theory is frequently used model such behaviour, it too time-consuming rapid assessment. In this paper, we explore use supervised machine learning predict whether dye titania likely induce a change its characteristics. The physicochemical...

To study the effect of π-spacers on dye performance in DSSC, five novel phenothiazine dyes have been prepared where number successive thiophenes π-spacer was increased from zero to four. Additionally, a bearing thieno[3,2-b]thiophene synthesized, and compared its unfused bithiophene analogue. When were two or more light absorption properties significantly better region 400–550 nm without π-spacer. DSSC device testing revealed that reference gave best overall producing power conversion...

The exposure of marine mammals to phthalates has received considerable attention due the ubiquitous occurrence these pollutants in environment and their potential adverse health effects. phthalate metabolites is well established human populations, but data scarce for mammals. In this study, concentrations 17 were determined liver samples collected from one hundred (n = 100) by-caught harbor porpoises (Phocoena phocoena) along coast Norway. Overall, thirteen detected samples. Monoethyl (mEP),...

Feature selection is a key step in Quantitative Structure Activity Relationship (QSAR) analysis. Chance correlations and multicollinearity are two major problems often encountered when attempting to find generalized QSAR models for use drug design. Optimal require an objective variable relevance analysis producing robust classifiers with low complexity good predictive accuracy. Genetic algorithms coupled information theoretic approaches such as mutual have been used near-optimal solutions...

Abstract Motivation: Aligning and comparing protein structures is important for understanding their evolutionary functional relationships. With the rapid growth of structure databases in recent years, need to align, superpose compare rapidly accurately has never been greater. Many structural alignment algorithms have described past 20 years. However, achieving an algorithm that both accurate fast remains a considerable challenge. Results: We developed novel called ‘Kpax’, which exploits...