Publications by authors named "B V Ravikumar"
A comparative assessment of the thermal properties and heat transfer coefficients achieved by viscoelastic nanofluids suitable for immersion cooling is presented, with the candidate samples exhibiting distinct differences based on the nanoparticle chemistry and shape. Molecular dynamics simulations of different nanoparticles such as copper nanosphere, two-dimensional pristine graphene, and single-walled carbon nanotube (CNT) dispersed in PAO-2 of concentrations of approximately equal to 2.6% by weight are performed in the present investigation.
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- Machine learning can effectively map how compounds interact with kinases, but varying types of bioactivity data (single-dose and multi-dose assays) complicate predictions.
- Traditional models focus only on multi-dose data, missing out on useful information from single-dose measurements.
- The proposed two-stage machine learning method combines both data types and shows significant improvements in prediction accuracy, achieving a 40% hit rate and enhanced performance across multiple machine learning techniques.
Aggregation of misfolded α-synuclein (α-syn) is a key characteristic feature of Parkinson's disease (PD) and related synucleinopathies. The nature of these aggregates and their contribution to cellular dysfunction is still not clearly elucidated. We employed mass spectrometry-based total and phospho-proteomics to characterize the underlying molecular and biological changes due to α-syn aggregation using the M83 mouse primary neuronal model of PD.
View Article and Find Full Text PDFAI for targeted polypharmacology: The next frontier in drug discovery.
Curr Opin Struct Biol
February 2024
Article Synopsis
- Targeted polypharmacology aims to create drugs that interact with multiple molecular targets, improving treatment for complex diseases while minimizing toxicity.
- Advances in artificial intelligence, particularly machine learning, are revolutionizing drug discovery by predicting drug interactions, modeling protein structures, and generating new compounds.
- The review highlights how AI can identify beneficial co-targets, differentiate them from harmful targets, and discusses the future challenges in implementing these technologies for effective multi-target drug design.*