Abstract
Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.
Highlights
Proteins are essential molecules involved in a wide variety of essential intra- and inter-cellular activities
The latest FunFOLD3 pipeline is composed of updated versions of two main algorithms, FunFOLD [4] and FunFOLDQA [1], and it produces output comprising predicted Enzyme Commission Numbers (EC) and Gene Ontology (GO) terms, ligand-binding site residues, putative ligands, binding site quality scores, and per-atom p-values to comply with the Continuous Automated Model EvaluatiOn (CAMEO)-LB format [65]
Assessment of protein–ligand binding site residue predictions have been carried out in CASP [8,75,76] and CAMEO [65] using a number of different scores, which include the Matthews Correlation Coefficient (MCC) [69] and the Binding-site Distance Test (BDT) score [68]
Summary
Proteins are essential molecules involved in a wide variety of essential intra- and inter-cellular activities. Studying protein–ligand binding sites and their associated residues, is an important step in the functional elucidation of proteins involved in these cellular processes [1,2,3,4]. TThhee PPllaassmmooddiiuumm vviivvaaxx TTRRAAPP pprrootteeiinn,, bboouunndd ttoo mmaaggnneessiiuumm,, iiss iinnvvoollvveedd iinnpphhoosspphhaatteeeesstteerrhhyyddrroollyyssiiss((FFiigguurree11CC))..FFiinnaallllyy,, FFiigguurree 11DD sshhoowwss tthhee pprrootteeiinn––lliiggaanndd bbiinnddiinngg ssiittee ooff tthhee aammiinnooppeeppttiiddaassee NN ffaammiillyy pprrootteeiinn QQ55QQTTYY11,, ffrroomm IIddiioommaarriinnaa llooiihhiieennssiiss bboouunndd ttoo zziinncc ((iittss ccooffaaccttoorr)),, wwhhiicchh ccaann bbee uusseedd aass aa bbiioommaarrkkeerr ttoo ddeetteecctt kkiiddnneeyy ddaammaaggee. IInn tthhiiss rreevviieeww,, tthhee tteerrmm lliiggaanndd iiss uusseedd ttoo rreeffeerr ttoo molecules capable of binding to a protein, such as metal ions, small organic (e.g., ATP) and inorganic compounds (e.g., NH4), peptides, and DNA/RN2A98; 3n0ot large macromolecules such as proteins. We discuss methods for the prediction of protein–ligand binding sites and their associated binding site residues. These methods can be broadly divided into sequence-based methods and structure-based methods
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