Automated docking is one of the most important tools for structure-based drug design that allows prediction of ligand binding poses and also provides an estimate of how well small molecules fit in the binding site of a protein. A new scoring function based on AutoDock and AutoDock Vina has been introduced. The new hybrid scoring function is a linear combination of the two scoring function components derived from a multiple linear regression fitting procedure. The scoring function was built on a training set of 2412 protein-ligand complexes from pdbbind database (www.pdbbind.org.cn, version 2012). A test set of 313 complexes that appeared in the 2013 version was used for validation purposes. The new hybrid scoring function performed better than the original functions, both on training and test sets of protein-ligand complexes, as measured by the non-parametric Pearson correlation coefficient, R, mean absolute error (MAE), and root-mean-square error (RMSE) between the experimental binding affinities and the docking scores. The function also gave one of the best results among more than 20 scoring functions tested on the core set of the pdbbind database. The new AutoDock hybrid scoring function will be implemented in modified version of AutoDock.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/cbdd.12697 | DOI Listing |
Scand J Med Sci Sports
January 2025
Department of Physical Education and Sports, Faculty of Sport Sciences, University of Granada, Melilla, Spain.
We aimed to determine the persisting effects of various exercise modalities and intensities on functional capacity after periods of training cessation in older adults. A comprehensive search was conducted across the Cochrane Library, PubMed/MEDLINE, Scopus, and Web of Science Core Collection up to March 2024 for randomized controlled trials examining residual effects of physical exercise on functional capacity in older adults ≥ 60 years. The analysis encompassed 15 studies and 21 intervention arms, involving 787 participants.
View Article and Find Full Text PDFCancer Med
January 2025
The Huntsman Cancer Institute at the University of Utah, Salt Lake City, Utah, USA.
Introduction: The purpose of this study was to evaluate the association between body composition, overall survival, odds of receiving treatment, and patient-reported outcomes (PROs) in individuals living with metastatic non-small-cell lung cancer (mNSCLC).
Methods: This retrospective analysis was conducted in newly diagnosed patients with mNSCLC who had computed-tomography (CT) scans and completed PRO questionnaires close to metastatic diagnosis date. Cox proportional hazard models and logistic regression evaluated overall survival and odds of receiving treatment, respectively.
Scand J Gastroenterol
January 2025
Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Xiamen Branch, Xiamen, China.
Background: Evaluate the clinical significance of esophagogastric junction (EGJ) morphology and esophagogastric junction contractile integral (EGJ-CI) in refractory gastroesophageal reflux disease (RGERD) patients.
Methods: From June 2021 to June 2023, 144 RGERD patients underwent comprehensive evaluation, recording symptom scores, demographic data. GERD classification (NERD or RE, A-D) was based on endoscopic findings.
Gut Microbes
December 2025
Division of Gastroenterology, Hepatology, and Nutrition, Virginia Commonwealth University and Richmond VA Medical Center, Richmond, VA, USA.
There is a complex interplay between the gut microbes, liver, and central nervous system, a gut-liver-brain axis, where the brain impacts intestinal and hepatic function while the gut and liver can impact cognition and mental status. Dysregulation of this axis can be seen in numerous diseases. Hepatic encephalopathy, a consequence of cirrhosis, is perhaps the best studied perturbation of this system.
View Article and Find Full Text PDFActa Radiol
January 2025
R Madhavan Nayar Center for Comprehensive Epilepsy Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India.
Background: The role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.
Purpose: To evaluate whether MRI is a diagnostic and prognostic marker for AIE and assess its efficacy in distinguishing between various AIE subtypes.
Material And Methods: We analyzed data from 96 AIE patients from our prospective autoimmune registry.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!