Results 191 to 200 of about 4,705,565 (247)

Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences

Advanced Science, EarlyView.
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu, Pan Zhang, Shangqian Wu, Hao Sun, Minwei Li, Sophia Tsoka, Zizhang Sheng, Lei Deng   +7 more
wiley   +1 more source

In Situ X‐Ray Tomography and Acoustic Emission Monitoring of Damage Evolution in C/C‐SiC Composites Fabricated by Liquid Silicon Infiltration

Advanced Science, EarlyView.
This study investigates how the internal structure of fiber‐reinforced ceramic composites affects their resistance to damage. By combining 3D X‐ray imaging with acoustic emission monitoring during mechanical testing, it reveals how silicon distribution influences crack formation.
Yang Chen, Renato S. M. Almeida, Stefan Flauder, Guillaume Couégnat, Kamen Tushtev, Jürgen Horvath, Peter Wriggers, Kurosch Rezwan   +7 more
wiley   +1 more source

Combating Inflammation and Promoting Anabolism in Osteoarthritic Cartilage Defect With an MMP13‐Sensing Dual‐Drug Scaffold

Advanced Science, EarlyView.
ABSTRACT Osteoarthritis (OA) is a widespread degenerative joint condition marked by progressive cartilage breakdown, and a chronic inflammatory microenvironment, where conventional therapies largely fail to halt disease progression. To address this unmet need, an intra‐articularly implantable, disease‐responsive scaffold was developed for combinatorial
Zhen Zhang, Bangheng Liu, Yulei Mu, Huiqun Zhou, Liang Ma, Chenjie Xu, Dong‐An Wang   +6 more
wiley   +1 more source

Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria

Advanced Science, EarlyView.
When a master transcription factor (TF) is lost, bacteria can rapidly rewire gene regulatory networks by co‐opting related regulators. Using experimental evolution in Pseudomonas fluorescens, we show that TF promiscuity (low‐level, non‐cognate binding) provides the raw material for rewiring. Successful co‐option follows a predictable hierarchy governed
Tiffany B. Taylor, Alan M. Rice
wiley   +1 more source

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source

Virtual Screening

, 2011
In this chapter, the authors analyze virtual screening advantages and the classification of virtual screening approaches. They also discuss the current and potential importance of virtual screening for drug development in Latin America. Finally, they present a brief overview on virtual screening perspectives.
Alan Talevi, Eduardo A. Castro, Luis E. Bruno-Blanch   +2 more
core   +5 more sources

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A framework for virtual screening

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016
Recent advances in Bioinformatics and in Computer simulation and modelling have positively impacted the drug discovery process by turning viable the rational drug design (RDD). One of the major challenges in RDD is the understanding about protein-ligand interaction simulated at the atomic level by molecular docking algorithms. Virtual screening (VS) is
Vinicius Rosa Seus, Lande Silva Jr., Jorge Gomes, Pedro E. A. da Silva, Adriano Velasque Werhli, Karina S. Machado   +5 more
openaire   +1 more source

Automated Virtual Screening

2023
Computational methods in modern drug discovery have become ubiquitous, with methods that cover most of the discovery stages: from hit finding and lead identification to lead optimization. The overall aim of these computational methods is to obtain a more efficient discovery process, by reducing the number of "wet" experiments required to produce ...
openaire   +2 more sources

Virtual Screening of Virtual Libraries

2003
Virtual screening of virtual libraries (VSVL) is a rapidly changing area of research. Great efforts are being made to produce better algorithms, selection methods and infrastructure. Yet, the number of successful examples in the literature is not impressive, although the quality of work certainly is high. Why is this?
openaire   +2 more sources

Virtual Screening: Are We There Yet?

Mini-Reviews in Medicinal Chemistry, 2006
The cost of pharmaceutical development has increased dramatically in recent years, and many assorted approaches have been developed to decrease both the time and costs associated with bringing a drug to the market. Among these methods is the use of in silico screening of compound databases for potential new lead compounds, commonly referred to as ...
Mehran, Jalaie, Veerabahu, Shanmugasundaram   +1 more
openaire   +2 more sources