Recent advances in computational methods for biosensor design. Issue 2 (17th November 2020) - Khoshbin, Zahra; Housaindokht, Mohammad R.; Izadyar, Mohammad; Bozorgmehr, Mohammad R.; Verdian, Asma
Abstract: Biosensors are analytical tools with a great application in healthcare, food quality control, and environmental monitoring. They are of considerable interest to be designed by using cost‐effective and efficient approaches. Designing biosensors with improved functionality or application in new target detection has been converted to a fast‐growing field of biomedicine and biotechnology branches. Experimental efforts have led to valuable successes in the field of biosensor design; however, some deficiencies restrict their utilization for this purpose. Computational design of biosensors is introduced as a promising key to eliminate the gap. A set of reliable structure prediction of the biosensor segments, their stability, and accurate descriptors of molecular interactions are required to computationally design biosensors. In this review, we provide a comprehensive insight into the progress of computational methods to guide the design and development of biosensors, including molecular dynamics simulation, quantum mechanics calculations, molecular docking, virtual screening, and a combination of them as the hybrid methodologies. By relying on the recent advances in the computational methods, an opportunity emerged for them to be complementary or an alternative to the experimental methods in the field of biosensor design. Abstract : The computational methods are introduced as the promising candidate to be a complement or a replacement for the experimental techniques to engineer biosensors. The successful computational design of the biosensors is dependent on the precise structural modeling, high biosensing components stability, and optimizing the molecular interactions. Molecular dynamics simulation, quantum mechanics calculations, molecular docking, virtual screening, and a combination of them, as the hybrid methodologies, are advantageous for the computational design of biosensors.