Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus in Silico Approaches

Version 1 : Received: 30 March 2024 / Approved: 1 April 2024 / Online: 1 April 2024 (12:43:09 CEST)

How to cite: Prieto-Martínez, F.D.; Mendoza-Cañas, J.; Martínez-Mayorga, K. To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus in Silico Approaches. Preprints 2024, 2024040052. https://doi.org/10.20944/preprints202404.0052.v1 Prieto-Martínez, F.D.; Mendoza-Cañas, J.; Martínez-Mayorga, K. To Bind or Not to Bind? A Comprehensive Characterization of TIR1 and Auxins Using Consensus in Silico Approaches. Preprints 2024, 2024040052. https://doi.org/10.20944/preprints202404.0052.v1

Abstract

Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Since the latter half of the XX century, synthetic auxins have been used as herbicides, presenting notable advantages, such as low toxicity in humans. As of today, extensive descriptions of syntetic and natural auxins have been made; yet studies centered on the molecular recognition process of auxins are scarce. Herein, we present a comprehensive in silico characterization of auxin receptor TIR1, using structure based methods to aid de novo design of putative ligands. In addition, we conducted binding site characterization using cosolvent molecular dynamics and enhanced sampling simulations with reference ligands. We also present a database of putative auxins and decoy compounds which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1.

Keywords

Herbicides; auxins; molecular dynamics; machine learning

Subject

Chemistry and Materials Science, Theoretical Chemistry

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