Endogenous Metabolic Modulators: Emerging Therapeutic Potential of Amino Acids

Abstract

Multifactorial disease pathophysiology is complex and incompletely addressed by existing targeted pharmacotherapies. Amino acids (AAs) and related metabolites and precursors are a class of endogenous metabolic modulators (EMMs) that have diverse biological functions and, thus, have been explored for decades as potential multifactorial disease treatments. Here, we review the literature on this class of EMMs in disease treatment, with a focus on the emerging clinical studies on AAs and related metabolites and precursors as single- and combination-agents targeted to a single biology. These clinical research insights, in addition to increasing understanding of disease metabolic profiles and combinatorial therapeutic design principles, highlight an opportunity to develop EMM compositions with AAs and related metabolites and precursors to target multifactorial disease biology. EMM compositions are uniquely designed to enable a comprehensive approach, with potential to simultaneously and safely target pathways underlying multifactorial diseases and to regulate biological processes that promote overall health.

Keywords: Health Sciences; Human Physiology; Pathophysiology.

Graphical abstract

Figure 1

Network Depiction of AA Interactions Built From Recon3D (A) Human metabolic network data from Recon3D. AAs in the network are shown on the left, and subsystems/pathways are shown on the right. The height of each box on the left representing each AA corresponds to the number of subsystems/pathways in which they are directly involved. The height of each box to the right represents each subsystem/pathway and corresponds to the number of connected AAs. (B) Human metabolic map highlighting AA connectivity to metabolites using Recon3D. Nodes correspond to reactants and products in Recon3D and are connected by edges (reactions) to construct a network graph. AAs are shown as blue nodes, and the first-degree metabolites, shown in orange, are directly involved in reactions with AAs. The sizes of the 20 AAs indicate the total number of first-degree metabolites associated with each AA, with the top five first-degree metabolites increased in size to reflect their connectivity. Second- and third-degree metabolites are two or three reaction edges away from AAs, respectively. For visualization purposes, seven highly structurally connected metabolite hubs (H⁺, H₂O, CO₂, phosphate, O₂, H₂O₂, O₇P₂) and transport subsystems were removed on the basis of a lack of significant functional connection within the network. (C) Distinct metabolites connected to AAs from first-, second-, and third-degree reactions. A, alanine; AA, amino acid; CoA, coenzyme A; C, cysteine; D, aspartate; E, glutamate; EMM, endogenous metabolic modulator; F, phenylalanine; G, glycine; H, histidine; I, isoleucine; K, lysine; L, leucine; M, methionine; N, asparagine; NAD, nicotinamide adenine dinucleotide; P, proline; Q, glutamine; R, arginine; S, serine; T, threonine; V, valine; W, tryptophan; Y, tyrosine.

Figure 2

Clinical Trials of AAs and Related Molecules Registered in Clinicaltrials.gov Between 2009 and 2019 We used natural-language processing to create a rank-scoring algorithm for clinicaltrials.gov, identifying relevant trials based on AAs and related metabolites and precursors of interest. Scores are calculated for each trial based on the terms of interest and their frequency. We used a hierarchical dictionary of inclusion and exclusion terms to rank order all trials and used a scoring threshold to identify high-scoring relevant trials. Inclusion criteria terms included specific EMM terms like alanine and glutamate. Exclusion criteria included terms that may have produced false-positive results, such as carbamylglutamate or norleucine. (A) Cumulative data for unique EMM trials and referenced MeSH terms each year. (B) The number of EMM trials initiated, EMMs studied, and unique MeSH terms referenced in studies from 2009 to 2019. (C) The 25 most commonly referenced MeSH terms related to the primary disease or condition being studied between 2009 and 2019. The legend is organized so that the MeSH terms are grouped by organ system or disease type, with nervous system-related terms shown first and metabolic-related terms shown second. The most common categories (≥4%) are labeled. (D) EMMs reported in clinical trials between 2009 and 2019. The legend is organized in order of frequency, and EMMs with ≥3% frequency are labeled. BCAA, branched-chain amino acid; EMM, endogenous metabolic modulator; HIV/AIDS, human immunodeficiency virus/acquired immunodeficiency syndrome; LOLA, L-ornithine and L-aspartate; NAC, N-acetyl cysteine; NAFLD, nonalcoholic fatty liver disease.

Figure 3

Rationally Designed EMM Compositions in the Treatment of Multifactorial Diseases A comprehensive understanding of AA activity combined with clinical insights on AAs and related metabolites and precursors and disease metabolite analysis enables combinatorial design strategies for selecting EMM compositions as multitargeted therapeutics. AA, amino acids; EMM, endogenous metabolic modulator; mRNA, messenger RNA; tRNA, tRNA.