Development of OTPD4ALS: A Specialized Database for Efficient Screening of Anti-amyotrophic Lateral Sclerosis Drug Candidates
Samuel Oluwaseun Ogunleye *
Department of Biochemistry, Applied Bioinformatics Research Laboratory, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Toheeb Olabisi Adeyeye
Department of Biochemistry, Applied Bioinformatics Research Laboratory, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Ifeoluwa Elizabeth Aderibigbe
Department of Biochemistry, Applied Bioinformatics Research Laboratory, Federal University Oye-Ekiti, Ekiti State, Nigeria.
Toluwase Hezekiah Fatoki *
Department of Biochemistry, Applied Bioinformatics Research Laboratory, Federal University Oye-Ekiti, Ekiti State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Amyotrophic lateral sclerosis (ALS) is a complex, multi-system disorder characterized by glial cell involvement, immune system dysfunction, axonal transport disturbances, and impaired mitochondrial and neurotrophic support. Developing a specialised database for the efficient screening and identification of potential anti-ALS compounds is essential for advancing therapeutic discovery. This study presents the design and development of OTPD4ALS (Open Targets Potential Drugs for ALS), a comprehensive database specifically tailored to accelerate the identification of promising drug candidates. The methodology involved curating potential compounds, predicting pharmacokinetics in batches, and structuring the database for optimal accessibility. OTPD4ALS provides a streamlined platform for quickly identifying potential therapeutic compounds and is publicly available at https://otpd4als.vercel.app.
Keywords: ALS, anti-ALS compounds, chemical database, MongoDB, JavaScript, TypeScript, React.js, Next.js, Node.js, pharmacokinetics