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AuthorAkawa, Oluwole B.
AuthorOkunlola, Felix O.
AuthorAlahmdi, Mohammed Issa
AuthorAbo-Dya, Nader E.
AuthorSidhom, Peter A.
AuthorIbrahim, Mahmoud A.A.
AuthorShibl, Mohamed F.
AuthorKhan, Shahzeb
AuthorSoliman, Mahmoud E.S.
Available date2025-10-09T04:55:59Z
Publication Date2024-01-31
Publication NameEuropean Journal of Pharmaceutics and Biopharmaceutics
Identifierhttp://dx.doi.org/10.1016/j.ejpb.2023.11.003
CitationAkawa, Oluwole B., Felix O. Okunlola, Mohammed Issa Alahmdi, Nader E. Abo-Dya, Peter A. Sidhom, Mahmoud AA Ibrahim, Mohamed F. Shibl, Shahzeb Khan, and Mahmoud ES Soliman. "Multi-cavity molecular descriptor interconnections: Enhanced protocol for prediction of serum albumin drug binding." European Journal of Pharmaceutics and Biopharmaceutics 194 (2024): 9-19.
ISSN09396411
URIhttps://www.sciencedirect.com/science/article/pii/S0939641123002928
URIhttp://hdl.handle.net/10576/67815
AbstractThe role of human serum albumin (HSA) in the transport of molecules predicates its involvement in the determination of drug distribution and metabolism. Optimization of ADME properties are analogous to HSA binding thus this is imperative to the drug discovery process. Currently, various in silico predictive tools exist to complement the drug discovery process, however, the prediction of possible ligand-binding sites on HSA has posed several challenges. Herein, we present a strong and deeper-than-surface case for the prediction of HSA-ligand binding sites using multi-cavity molecular descriptors by exploiting all experimentally available and crystallized HSA-bound drugs. Unlike previously proposed models found in literature, we established an in-depth correlation between the physicochemical properties of available crystallized HSA-bound drugs and different HSA binding site characteristics to precisely predict the binding sites of investigational molecules. Molecular descriptors such as the number of hydrogen bond donors (nHD), number of heteroatoms (nHet), topological polar surface area (TPSA), molecular weight (MW), and distribution coefficient (LogD) were correlated against HSA binding site characteristics, including hydrophobicity, hydrophilicity, enclosure, exposure, contact, site volume, and donor/acceptor ratio. Molecular descriptors nHD, TPSA, LogD, nHet, and MW were found to possess the most inherent capacities providing baseline information for the prediction of serum albumin binding site. We believe that these associations may form the bedrock for establishing a solid correlation between the physicochemical properties and Albumin binding site architecture. Information presented in this report would serve as critical in provisions of rational drug designing as well as drug delivery, bioavailability, and pharmacokinetics.
Languageen
PublisherElsevier
SubjectHuman serum albumin
Physicochemical properties
Drug binding
HSA prediction models
Molecular descriptors
TitleMulti-cavity molecular descriptor interconnections: Enhanced protocol for prediction of serum albumin drug binding
TypeArticle
Pagination9-19
Volume Number194
ESSN1873-3441
dc.accessType Open Access


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