98%
921
2 minutes
20
Drug development is one of the most significant processes in the pharmaceutical industry. Various computational methods have dramatically reduced the time and cost of drug discovery. In this review, we firstly discussed roles of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms. Then, virtual screening methods (e.g., molecular docking, pharmacophore modeling, and QSAR) as well as structure- and ligand-based classical/de novo drug design were introduced and discussed. Last, we explored the development of machine learning methods and their applications in aforementioned computational methods to speed up the drug discovery process. Also, several application examples of combining various methods was discussed. A combination of different methods to jointly solve the tough problem at different scales and dimensions will be an inevitable trend in drug screening and design.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144386 | PMC |
http://dx.doi.org/10.3390/molecules25061375 | DOI Listing |
Obesity (Silver Spring)
September 2025
Division of Hematology, Oncology, and Palliative Care, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, USA.
Objective: From October 18-20, 2022, the National Institutes of Health held a workshop to examine the state of the science concerning obesity interventions in adults to promote health equity. The workshop had three objectives: (1) Convene experts from key institutions and the community to identify gaps in knowledge and opportunities to address obesity, (2) generate recommendations for obesity prevention and treatment to achieve health equity, and (3) identify challenges and needs to address obesity prevalence and disparities, and develop a diverse workforce.
Methods: A three-day virtual convening.
Front Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.
iScience
September 2025
Max Planck Institute of Psychiatry, 80804 Munich, Germany.
Isoform-specific expression patterns have been linked to stress-related psychiatric disorders such as major depressive disorder (MDD). To further explore their involvement, we constructed co-expression networks using total gene expression (TE) and isoform ratio (IR) data from affected ( = 210, 81% with depressive symptoms) and unaffected ( = 95) individuals. Networks were validated using advanced graph generation methods.
View Article and Find Full Text PDFLancet Reg Health West Pac
September 2025
Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China.
Background: There is ongoing controversy as to whether surgical intervention to haematoma evacuation benefits patients with acute intracerebral haemorrhage (ICH). This study aimed to evaluate the association of surgical intervention to evacuate the haematoma and 6-month functional outcome in participants of the third Intensive Care Bundle with Blood Pressure Reduction in Acute Cerebral Haemorrhage Trial (INTERACT3).
Methods: This was a secondary analysis of INTERACT3, which enrolled adults (age ≥18 years) spontaneous ICH patients within 6 h after onset.
J Biomed Opt
September 2025
Fraunhofer Institute for Microelectronic Circuits and Systems IMS, Duisburg, Germany.
Significance: The spatial and temporal distribution of fluorophore fractions in biological and environmental systems contains valuable information about the interactions and dynamics of these systems. To access this information, fluorophore fractions are commonly determined by means of their fluorescence emission spectrum (ES) or lifetime (LT). Combining both dimensions in temporal-spectral multiplexed data enables more accurate fraction determination while requiring advanced and fast analysis methods to handle the increased data complexity and size.
View Article and Find Full Text PDF