Abstract
Tissue level expression, mutation, and substrate specificity of the transporter proteins have been widely accepted for their usefulness in drug disposition and efficacy. Many transporters play a significant role in normal human physiology as well as in disease conditions. Association of these properties, with systemic plasma concentration of the drug, is the leading reason for adverse drug reactions and drug resistance. The identification and validation of transporter proteins in experiments and their atomic resolution for characterization of structural-functional relationship is a costly, time-consuming, and more tedious process. However, predictive in silico tools claimed well for accurately accessing the pharmacokinetics, pharmacodynamics properties in early drug discovery stage. But the huge amount of data requires the development of reliable computational techniques and databases for the identification and/or prediction of membrane transport proteins as well as their ligands has become essential. Here, we review the available datasets and the computational methods, which put forth more insights for better understanding of human drug transporter proteins.
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The authors are thankful to the Indian Council of Medical Research (ICMR) and the Department of Biotechnology (DBT), Government of India, for financial assistance.
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Singla, D., Bishnoi, R., Dhanda, S.K., Asthana, S. (2018). Drug Transporters as Therapeutic Targets: Computational Models, Challenges, and Future Perspective. In: Purohit, H., Kalia, V., More, R. (eds) Soft Computing for Biological Systems. Springer, Singapore. https://doi.org/10.1007/978-981-10-7455-4_9
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