How ‘Protein-Docking’ Translates into the New Emerging Field of Docking Small Molecules to Nucleic Acids?

Abstract

In this review, we retraced the ‘40-year evolution’ of molecular docking algorithms. Over the course of the years, their development allowed to progress from the so-called ‘rigid-docking’ searching methods to the more sophisticated ‘semi-flexible’ and ‘flexible docking’ algorithms. Together with the advancement of computing architecture and power, molecular docking’s applications also exponentially increased, from a single-ligand binding calculation to large screening and polypharmacology profiles. Recently targeting nucleic acids with small molecules has emerged as a valuable therapeutic strategy especially for cancer treatment, along with bacterial and viral infections. For example, therapeutic intervention at the mRNA level allows to overcome the problematic of undruggable proteins without modifying the genome. Despite the promising therapeutic potential of nucleic acids, molecular docking programs have been optimized mostly for proteins. Here, we have analyzed literature data on nucleic acid to benchmark some of the widely used docking programs. Finally, the comparison between proteins and nucleic acid targets docking highlighted similarity and differences, which are intrinsically related to their chemical and structural nature.

Role and Perspective of Molecular Simulation-Based Investigation of RNA–Ligand Interaction: From Small Molecules and Peptides to Photoswitchable RNA Binding

“…However, while the binding pocket of proteins usually lie in an internal region sufficiently separated from solvents, in RNA the binding pockets are usually large and flat, located along the surface, and relatively exposed to solvents [ 56 ]. Therefore, properties of RNA such as conformational flexibility, high negative charge, and solvation might challenge both docking algorithms and molecular dynamics approaches [ 56 , 57 ]. Many of the currently available docking programs, initially designed for protein/protein or protein/ligand docking, have been adapted or reparametrized to enable RNA–ligand docking (i.e., Dock6 [ 58 ], ICM [ 59 ], or AutoDock [ 60 ]).…”

RNA–ligand molecular docking: Advances and challenges

“…According to their cellular functions, RNA molecules can be categorized into two types: messenger (coding) RNAs (mRNAs) that encode the amino acid sequences and are translated into proteins, and noncoding RNAs (ncRNAs), which, instead of encoding amino acid sequence, serve as enzymatic, structural, and regulatory elements for gene expression. With the coding RNAs occupying only <3% of the human genome, 1–3 the vast majority of the human genome sequences are transcribed to ncRNAs, such as ribosomal RNAs (rRNAs), microRNAs (miRNAs), small interfering RNAs (siRNAs), small nuclear RNAs (snRNAs), and various riboswitches 4,5 . With the ever increasing discoveries of new RNA structures and cellular functions and the continuous developments of powerful RNA structure determination methods, RNA‐based therapeutics are becoming new promising methods to treat human disease.…”

“…2,[9][10][11][12][13][14][15] This second approach is analogous to protein-targeted drug discovery. However, only approximately 1.5% of the human genome encodes protein, 2,3,13,[16][17][18] and of these protein-encoding genes, only 10%-15% are disease-related. 2,3,13,[19][20][21] The availability of druggable protein targets is further restricted by the structural and energetic fitness required for high-affinity drug binding.…”

“…However, only approximately 1.5% of the human genome encodes protein, 2,3,13,[16][17][18] and of these protein-encoding genes, only 10%-15% are disease-related. 2,3,13,[19][20][21] The availability of druggable protein targets is further restricted by the structural and energetic fitness required for high-affinity drug binding. In contrast, genes that are undruggable or difficult to drug by targeting their associated proteins may be inhibited by drugs targeting the corresponding mRNA sequence.…”

“…[55][56][57][58] Second, RNA molecules are often quite flexible, capable of folding into multiple stable conformations, and ligand binding often induces structural switches between different conformers or change the structure of an RNA receptor. Compared with protein-ligand binding, ligand binding sites on RNA can be less deep and more polar, solvated, and conformationally flexible, 3,11,58 which adds further complexity to predicting RNA-small molecule interactions. Third, the fact that we have a limited number of experimentally determined structures for RNA molecules and RNA-ligand complexes makes pure knowledge-based approaches less effective for RNA-ligand predictions.…”