Applications and Potential of In Silico Approaches for Psychedelic Chemistry

Abstract

Molecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and in vitro drug tests. In this review, we explore how computational methods and informatics have contributed to our understanding of mental health disorders and the development of novel drugs for neurological diseases, with a special focus on the emerging field of psychedelics. In addition, the use of state-of-the-art computational methods to predict the potential of drug compounds and bioinformatic tools to integrate disparate data sources to create predictive models is also discussed. Furthermore, the challenges associated with these methods, such as the need for large datasets and the diversity of in vitro data, are explored. Overall, this review highlights the immense potential of computational methods and informatics in Central Nervous System research and underscores the need for continued development and refinement of these techniques and more inclusion of Quantitative Structure-Activity Relationships (QSARs).

Keywords: Central Nervous System; MDMA; Structure-Activity Relationship (SAR); artificial intelligence; computational modeling; docking; dopamine; in silico; machine learning; molecular dynamics; psychedelics; quantum mechanics/molecular mechanics (QM/MM); serotonin.

Figure 1

A general overview of monoamine transportation.

Figure 2

Timeline of key events in computational psychedelic sciences [20,21].

Figure 3

The purple dashed line represents the total number of publication hits, for 2015–2022, on Scopus for studies that also contained one or more of the terms “CNS”, “serotonin”, “dopamine”, or “norepinephrine” as of 20 March 2023 (right ordinate). Each column, within a given year, indicates the number of publications (within the same above search criteria, left ordinate) that also include the related in silico terms “Computational”, “DFT”, “Molecular Dynamics”, and/or “QSAR”.

Figure 4

A multi-scale computational approach is generally used for enzyme mechanism studies.

Figure 5

Metabolic degradation of histamine (HIS) to the corresponding aldehyde by MAO, but only after HIS is converted to N-methylhistamine (NMH) with histamine methyltransferase (HMT).

Figure 6

Schematic illustration of two proposed mechanisms of aromatic hydroxylation of Tyramine by Cpd 1, as proposed via (a) a Meisenheimer-complex mechanism and (b) a radical [65,66].

Figure 7

The molecular structures, showing their stereoisomers, of several important cathinones and amphetamine analogs (R-MDMA docked within the central binding site of SERT) are provided in Figure S1.