Results 61 to 70 of about 24,906 (269)

In Silico Studies of Lamiaceae Diterpenes with Bioinsecticide Potential against Aphis gossypii and Drosophila melanogaster

Molecules, 2021
Background: The growing demand for agricultural products has led to the misuse/overuse of insecticides; resulting in the use of higher concentrations and the need for ever more toxic products. Ecologically, bioinsecticides are considered better and safer
Gabriela Cristina Soares Rodrigues, Mayara dos Santos Maia, Andreza Barbosa Silva Cavalcanti, Natália Ferreira de Sousa, Marcus Tullius Scotti, Luciana Scotti   +5 more
doaj   +1 more source

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

, 2013
Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly ...
Bird, Colin, Frey, Jeremy G.
core   +1 more source

TeachOpenCADD: a teaching platform for computer-aided drug design using open source packages and data [PDF]

, 2019
Owing to the increase in freely available software and data for cheminformatics and structural bioinformatics, research for computer-aided drug design (CADD) is more and more built on modular, reproducible, and easy-to-share pipelines.
Driller, Maximilian, Morger, Andrea, Sydow, Dominique, Volkamer, Andrea   +3 more
core   +1 more source

Deep Learning Approach for Predicting Efficiency in Organic Photovoltaics from 2D Molecular Images of D/A Pairs

Advanced Theory and Simulations, EarlyView.
This study highlights the potential of deep learning, particularly Convolutional Neural Networks (CNNs), for predicting the photovoltaic performance of organic solar cells. By leveraging 2D images representing donor/acceptor molecular pairs, the model accurately estimates key performance indicators proving that this image‐based approach offers a fast ...
Khoukha Khoussa, Patrick Lévêque, Larbi Boubchir   +2 more
wiley   +1 more source

Utilizing Molecular Descriptor Importance to Enhance Endpoint Predictions

Toxics
Quantitative structure–activity relationship (QSAR) models are essential for predicting endpoints that are otherwise challenging to estimate using other in silico approaches.
Benjamin Bajželj, Marjana Novič, Viktor Drgan   +2 more
doaj   +1 more source

An In Silico Approach for Assessment of the Membrane Transporter Activities of Phenols: A Case Study Based on Computational Models of Transport Activity for the Transporter Bilitranslocase

Molecules, 2019
Phenols are the most abundant naturally accessible antioxidants present in a human normal diet. Since numerous beneficial applications of phenols as preventive agents in various diseases were revealed, the evaluation of phenols bioavailability is of high
Katja Venko, Marjana Novič
doaj   +1 more source

In-silico Predictive Mutagenicity Model Generation Using Supervised Learning Approaches [PDF]

, 2011
With the advent of High Throughput Screening techniques, it is feasible to filter possible leads from a mammoth chemical space that can act against a particular target and inhibit its action.
Abhik Seal, Abhik Seal, Anurag Passi, OSDD Consortium, UC Abdul Jaleel   +4 more
core   +2 more sources

Comparative Analyses of Medicinal Chemistry and Cheminformatics Filters with Accessible Implementation in Konstanz Information Miner (KNIME)

International Journal of Molecular Sciences, 2022
High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics.
Sebastjan Kralj, M. Jukič, U. Bren
semanticscholar   +1 more source

Learned Conformational Space and Pharmacophore Into Molecular Foundational Model

Advanced Science, EarlyView.
The Ouroboros model introduces two orthogonal modules within a unified framework that independently learn molecular representations and generate chemical structures. This design enables flexible optimization strategies for each module and faithful structure reconstruction without prompts or noise.
Lin Wang, Yifan Wu, Hao Luo, Minglong Liang, Yihang Zhou, Cheng Chen, Chris Liu, Jun Zhang, Yang Zhang   +8 more
wiley   +1 more source

Unveiling the Potent Antiviral and Antioxidant Activities of an Aqueous Extract from Caesalpinia mimosoides Lamk: Cheminformatics and Molecular Docking Approaches

Foods, 2023
Our group previously demonstrated that Caesalpinia mimosoides Lamk exhibits many profound biological properties, including anticancer, antibacterial, and antioxidant activities. However, its antiviral activity has not yet been investigated.
Anuwatchakij Klamrak, Jaran Nabnueangsap, Jaraspim Narkpuk, Yutthakan Saengkun, Piyapon Janpan, Napapuch Nopkuesuk, Arunrat Chaveerach, Samaporn Teeravechyan, Shaikh Shahinur Rahman, Theerawat Dobutr, Poramet Sitthiwong, Pornsuda Maraming, Natsajee Nualkaew, Nisachon Jangpromma, Rina Patramanon, Sakda Daduang, Jureerut Daduang   +16 more
doaj   +1 more source