Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases

Abstract

Computer-aided drug design (CADD) techniques allow the identification of compounds capable of modulating protein functions in pathogenesis-related pathways, which is a promising line on drug discovery. Marine natural products (MNPs) are considered a rich source of bioactive compounds, as the oceans are home to much of the planet's biodiversity. Biodiversity is directly related to chemodiversity, which can inspire new drug discoveries. Therefore, natural products (NPs) in general, and MNPs in particular, have been used for decades as a source of inspiration for the design of new drugs. However, NPs present both opportunities and challenges. These difficulties can be technical, such as the need to dive or trawl to collect the organisms possessing the compounds, or biological, due to their particular marine habitats and the fact that they can be uncultivable in the laboratory. For all these difficulties, the contributions of CADD can play a very relevant role in simplifying their study, since, for example, no biological sample is needed to carry out an in-silico analysis. Therefore, the amount of natural product that needs to be used in the entire preclinical and clinical study is significantly reduced. Here, we exemplify how this combination between CADD and MNPs can help unlock their therapeutic potential. In this study, using a set of marine invertebrate molecules, we elucidate their possible molecular targets and associated therapeutic potential, establishing a pipeline that can be replicated in future studies.

Keywords: cardiovascular diseases; computer-aided drug design; marine natural products; neurodegenerative diseases; virtual profiling.

Figure 1

Schematic pipeline of the Drug Discovery cycle highlighting where CADD techniques are used.

Figure 2

(A) Structures of the ten marine molecules selected for this study (B) Graphical representation of the workflow process followed to the exploration of all set of marine molecules.

Figure 3

Relation between selected targets and analyzed pathologies. Yellow: neurodegenerative, Grey: cardiovascular, Orange; Neurodegenerative and cardiovascular, Purple: Other pathologies.

Figure 4

The graph shows the hydrogen bond (HB) occupancy per target. Only the best molecule–target complexes (Table S5) are reported. Residue numbers correspond to Wild Type sequence numbering from Uniprot. All those occupancies lower than 0.99% were not taken into account and are not shown. Horizontal numbers are the Uniprot ID, and vertical letters and numbers refer to the residue involved on the HB of each target. If a residue appears several times it means that different HBs have been detected between the ligand and the residue.

Figure 5

Images of the binding mode of each marine molecule inside the binding cavity of the corresponding target (last frame of the trajectory). Marine molecules and interacting residues are represented in sticks, while proteins are shown as cartoons. Orange lines indicate HBs, grey dashed lines hydrophobic interactions. Binding energies obtained by MM/GBSA calculations are reported next to the target name.