Journal of chemical information and modeling
36373285
Malaria is a threatening disease that has claimed many lives and has a high prevalence rate annually. Through the past decade, there have been many studies to uncover effective antimalarial compounds to combat this disease. Alongside chemically synth...
ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (Copilot, GPT-3.5, and GPT-4) on antimalarial use in systemic lupus erythematosus (SLE).Materials and MethodsWe utilized 13 questions derived from pati...
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
International journal of molecular sciences
34884870
The parasite species of genus causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds...
Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework, MalariaSE...
PURPOSE: Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation o...
Journal of chemical information and modeling
39013438
Computational approaches are widely applied in drug discovery to explore properties related to bioactivity, physiochemistry, and toxicology. Over at least the last 20 years, the exploitation of machine learning on molecular data sets has been used to...
Malaria remains a significant global health challenge due to the growing drug resistance of Plasmodium parasites and the failure to block transmission within human host. While machine learning (ML) and deep learning (DL) methods have shown promise in...
Generative machine learning models offer a novel strategy for chemogenomics and de novo drug design, allowing researchers to streamline their exploration of the chemical space and concentrate on specific regions of interest. In cases with limited inh...
BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence...