Prioritisation of Promising Therapeutic Targets in Plasmodium falciparum Using in Silico Multi Criteria Scoring
Mamadou Sangare
Laboratory of Malaria and Vector Research (LMVR), National Institute of Allergy and Infectious Diseases (NIAID), Mali.
Cheickna Cisse
African Center of Excellence in Bioinformatics and data science (ACE-B), University of Sciences, Techniques and Technologies of Bamako (USTTB), Mali.
Bakary N'tji Diallo
Malaria Research and Training Centre-International Center for Excellence in Research (MRTC-ICER), University of Science Techniques and Technologies of Bamako (USTTB), Mali.
Alia Benkahla
Laboratory of Bioinformatics, Biomathematics and Biostatistics (BIMS), Institut Pasteur de Tunis, Tunisia.
Jian Li
School of Public Health and Tropical Medicine, Tulane university, New Orleans, Louisiana, USA.
Jeffrey G Shaffer
School of Public Health and Tropical Medicine, Tulane university, New Orleans, Louisiana, USA.
Seydou Doumbia
University Clinical Research Center (UCRC), University of Sciences, Techniques and Technologies of Bamako (USTTB), Mali.
Annie Degroot
Epivax, Inc. 188 Valley Street Providence, RI 02909, USA.
Mamadou Wele
*
African Center of Excellence in Bioinformatics and data science (ACE-B), University of Sciences, Techniques and Technologies of Bamako (USTTB), Mali.
*Author to whom correspondence should be addressed.
Abstract
Background: Malaria remains one of the deadliest infectious diseases globally, causing over 597,000 deaths each year, with Plasmodium falciparum (Pf) responsible for the most severe cases. Sub-Saharan Africa remains the most affected region of the world, the region hosting more than 90% of the global burden of P. falciparum. Despite years of research, drug resistance continues to emerge, underscoring the urgent need for new therapeutic targets.
Aim: The aim of this study is to identify promising therapeutic targets in Plasmodium falciparum using advanced in silico approaches. This study focuses particularly on the intraerythrocytic stage of the parasite's life cycle, which is critical for its survival and proliferation.
Methodology: A comprehensive bioinformatics approach was employed, integrating data mining and extensive database analyses to efficiently streamline the drug discovery pipeline and pinpoint vital therapeutic targets in Plasmodium falciparum. Analyses were carried out from January to June 2022 at the African Centre of Excellence in Bioinformatics (ACE-Mali), using data from the TDR Targets database and advanced bioinformatics tools. The WHO validated TDR Targets database was used to extract Plasmodium falciparum proteins likely to be therapeutic targets, applying strict criteria such as strong expression during the intra-erythrocytic stage, lack of human orthologs, essentiality, druggability score and bibliographic support. This candidate list has been refined using an in-house scoring system combining bioinformatics analyses, taking into account criteria such as the presence of transmembrane helices, sequence identity, and conservation. Each criterion was scored from 0 to 3 and summed into an overall prioritisation score to systematically rank proteins.
Results: The study identified sixteen potential therapeutic targets, with five of them: Adenylate kinase, P. falciparum Chloroquine Resistance Transporter (PfCRT), AdenyloSuccinate Lyase (ADSL), PhosphatidylSerine Decarboxylase (PSD), and Protein Disulfide Isomerase (PDI), highlighted as highly promising. These key proteins are involved in essential processes such as invasion, replication, and immune evasion of the malaria parasite.
Conclusion: This study identified sixteen potential therapeutic targets against malaria, with Adenylate kinase, PfCRT, ADSL, PSD, and PDI standing out as particularly promising. These targets may contribute to overcoming drug resistance and support global eradication efforts. The findings highlight the power of in silico approaches in accelerating drug discovery and target validation.
Keywords: P. falciparum, TDR targets, therapeutic targets, drug resistance, in silico approaches, intraerythrocytic stage