Search results for "Virtual"
showing 10 items of 1485 documents
Il contributo delle tecnologie digitali per la valorizzazione del patrimonio rupestre pugliese
2016
The essay concerns the recent work carried out as part of a multidisciplinary research on some rocky churches in the southern Apulia, conducted in collaboration with the Chair of History of Medieval Art of the University of Salento and of the University of Bari. The work aims at the knowledge and the monitoring of the fresco paintings inside three rocky environments, two of which are located in Lama d’Antico, in Fasano (BR), and the other two in Vaste di Poggiardo and Giurdignano (LE). The contribution illustrates methods and data acquired during the fieldwork, carried out through a multidisciplinary approach. From the image-based Techniques for the survey in Camera-Scanner to the restituti…
2019
Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein’s ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer…
A Molecular Dynamics-Shared Pharmacophore Approach to Boost Early-Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator-Activated Rec…
2016
Molecular dynamics (MD) simulations can be used, prior to virtual screening, to add flexibility to proteins and study them in a dynamic way. Furthermore, the use of multiple crystal structures of the same protein containing different co-crystallized ligands can help elucidate the role of the ligand on a protein's active conformation, and then explore the most common interactions between small molecules and the receptor. In this work, we evaluated the contribution of the combined use of MD on crystal structures containing the same protein but different ligands to examine the crucial ligand-protein interactions within the complexes. The study was carried out on peroxisome proliferator-activat…
A Comparative Study of Nonlinear Machine Learning for the "In Silico" Depiction of Tyrosinase Inhibitory Activity from Molecular Structure.
2011
In the preset report, for the first time, support vector machine (SVM), artificial neural network (ANN), Baye- sian networks (BNs), k-nearest neighbor (k-NN) are applied and compared on two "in-house" datasets to describe the tyrosinase inhibitory activity from the molecular structure. The data set Data I is used for the identification of tyrosi- nase inhibitors (TIs) including 701 active and 728 inactive compounds. Data II consists of active chemicals for potency estimation of TIs. The 2D TOMOCOMD-CARDD atom-based quadratic indices are used as molecular descriptors. The de- rived models show rather encouraging results with the areas under the Receiver Operating Characteristic (AURC) curve …
Topological virtual screening: a way to find new anticonvulsant drugs from chemical diversity.
2003
A topological virtual screening (tvs) test is presented, which is capable of identifying new drug leaders with anticonvulsant activity. Molecular structures of both anticonvulsant-active and non active compounds, extracted from the Merck Index database, were represented using topological indexes. By means of the application of a linear discriminant analysis to both sets of structures, a topological anticonvulsant model (tam) was obtained, which defines a connectivity function. On the basis of this model, 41 new structures with anticonvulsant activity have been identified by a topological virtual screening.
An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking
2019
Thermolysin is a bacterial proteolytic enzyme, considered by many authors as a pharmacological and biological model of other mammalian enzymes, with similar structural characteristics, such as angiotensin converting enzyme and neutral endopeptidase. Inhibitors of these enzymes are considered therapeutic targets for common diseases, such as hypertension and heart failure. In this report, a mathematical model of Multiple Linear Regression, for ordinary least squares, and genetic algorithm, for selection of variables, are developed and implemented in QSARINS software, with appropriate parameters for its fitting. The model is extensively validated according to OECD standards, so that its robust…
Convolutional architectures for virtual screening
2020
Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …
Improving structural similarity based virtual screening using background knowledge
2013
Background Virtual screening in the form of similarity rankings is often applied in the early drug discovery process to rank and prioritize compounds from a database. This similarity ranking can be achieved with structural similarity measures. However, their general nature can lead to insufficient performance in some application cases. In this paper, we provide a link between ranking-based virtual screening and fragment-based data mining methods. The inclusion of binding-relevant background knowledge into a structural similarity measure improves the quality of the similarity rankings. This background knowledge in the form of binding relevant substructures can either be derived by hand selec…
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability.
2016
Background Even though circular fingerprints have been first introduced more than 50 years ago, they are still widely used for building highly predictive, state-of-the-art (Q)SAR models. Historically, these structural fragments were designed to search large molecular databases. Hence, to derive a compact representation, circular fingerprint fragments are often folded to comparatively short bit-strings. However, folding fingerprints introduces bit collisions, and therefore adds noise to the encoded structural information and removes its interpretability. Both representations, folded as well as unprocessed fingerprints, are often used for (Q)SAR modeling. Results We show that it can be prefer…
Application of molecular topology to the prediction of inhibition of Trypanosoma cruzi Hexokinase by bisphosphonates
2008
Se ha desarrollado un modelo topológico-matemático para la búsqueda de nuevos derivados bisfosfonatos activos frente a la hexokinasa de Trypanosoma cruzi. Utilizando el análisis lineal discriminante se ha seleccionado una función con cuatro variables capaz de predecir adecuadamente la CI50 para cada compuesto de las series de entrenamiento y test. El modelo propuesto se ha aplicado a una librería molecular y se han propuesto nuevas estructuras potencialmente activas frente a T. cruzi.