Structural bioinformatics is the branch of bioinformatics that is related to the analysis and prediction of the three-dimensional structure of biological macromolecules such as proteins, RNA, and DNA. It deals with generalizations about macromolecular 3D structures such as comparisons of overall folds and local motifs, principles of molecular folding, evolution, binding interactions, and structure/function relationships, working both from experimentally solved structures and from computational models. The term structural has the same meaning as in structural biology, and structural bioinformatics can be seen as a part of computational structural biology. The main objective of structural bioinformatics is the creation of new methods of analysing and manipulating biological macromolecular data in order to solve problems in biology and generate new knowledge.
Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals including peptides and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.
In biochemistry and pharmacology, a ligand is a substance that forms a complex with a biomolecule to serve a biological purpose. The etymology stems from Latin ligare, which means 'to bind'. In protein-ligand binding, the ligand is usually a molecule which produces a signal by binding to a site on a target protein. The binding typically results in a change of conformational isomerism (conformation) of the target protein. In DNA-ligand binding studies, the ligand can be a small molecule, ion, or protein which binds to the DNA double helix. The relationship between ligand and binding partner is a function of charge, hydrophobicity, and molecular structure.
In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when a ligand and a target are bound to each other to form a stable complex. Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using, for example, scoring functions.
OpenEye Scientific Software is an American software company founded by Anthony Nicholls in 1997. It develops large-scale molecular modelling applications and toolkits. Following OpenEye's acquisition by Cadence Design Systems for $500 million in September 2022, the company was rebranded to OpenEye Cadence Molecular Sciences and operates as a business unit under Cadence.
Rosetta@home is a volunteer computing project researching protein structure prediction on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, run by the Baker lab. Rosetta@home aims to predict protein–protein docking and design new proteins with the help of about fifty-five thousand active volunteered computers processing at over 487,946 GigaFLOPS on average as of September 19, 2020. Foldit, a Rosetta@home videogame, aims to reach these goals with a crowdsourcing approach. Though much of the project is oriented toward basic research to improve the accuracy and robustness of proteomics methods, Rosetta@home also does applied research on malaria, Alzheimer's disease, and other pathologies.
Protein–ligand docking is a molecular modelling technique. The goal of protein–ligand docking is to predict the position and orientation of a ligand when it is bound to a protein receptor or enzyme. Pharmaceutical research employs docking techniques for a variety of purposes, most notably in the virtual screening of large databases of available chemicals in order to select likely drug candidates. There has been rapid development in computational ability to determine protein structure with programs such as AlphaFold, and the demand for the corresponding protein-ligand docking predictions is driving implementation of software that can find accurate models. Once the protein folding can be predicted accurately along with how the ligands of various structures will bind to the protein, the ability for drug development to progress at a much faster rate becomes possible.
In molecular modelling, docking is a method which predicts the preferred orientation of one molecule to another when bound together in a stable complex. In the case of protein docking, the search space consists of all possible orientations of the protein with respect to the ligand. Flexible docking in addition considers all possible conformations of the protein paired with all possible conformations of the ligand.
In the fields of computational chemistry and molecular modelling, scoring functions are mathematical functions used to approximately predict the binding affinity between two molecules after they have been docked. Most commonly one of the molecules is a small organic compound such as a drug and the second is the drug's biological target such as a protein receptor. Scoring functions have also been developed to predict the strength of intermolecular interactions between two proteins or between protein and DNA.
Ephrin type-B receptor 3 is a protein that in humans is encoded by the EPHB3 gene.
Molecular design software is notable software for molecular modeling, that provides special support for developing molecular models de novo.
Docking@Home was a volunteer computing project hosted by the University of Delaware and running on the Berkeley Open Infrastructure for Network Computing (BOINC) software platform. It models protein-ligand docking using the CHARMM program. Volunteer computing allows an extensive search of protein-ligand docking conformations and selection of near-native ligand conformations are achieved by using ligand based hierarchical clustering. The ultimate aim was the development of new pharmaceutical drugs.
AutoDock is a molecular modeling simulation software. It is especially effective for protein-ligand docking. AutoDock 4 is available under the GNU General Public License. AutoDock is one of the most cited docking software applications in the research community. It is used by the FightAIDS@Home and OpenPandemics - COVID-19 projects run at World Community Grid, to search for antivirals against HIV/AIDS and COVID-19. In February 2007, a search of the ISI Citation Index showed more than 1,100 publications had been cited using the primary AutoDock method papers. As of 2009, this number surpassed 1,200.
Lead Finder is a computational chemistry tool designed for modeling protein-ligand interactions. This application is useful for conducting molecular docking studies and quantitatively assessing ligand binding and biological activity. Lead Finder offers free access to individual users, especially those in non-commercial and academic settings.
Discovery Studio is a suite of software for simulating small molecule and macromolecule systems. It is developed and distributed by Dassault Systemes BIOVIA.
Molecular Operating Environment (MOE) is a drug discovery software platform that integrates visualization, modeling and simulations, as well as methodology development, in one package. MOE scientific applications are used by biologists, medicinal chemists and computational chemists in pharmaceutical, biotechnology and academic research. MOE runs on Windows, Linux, Unix, and macOS. Main application areas in MOE include structure-based design, fragment-based design, ligand-based design, pharmacophore discovery, medicinal chemistry applications, biologics applications, structural biology and bioinformatics, protein and antibody modeling, molecular modeling and simulations, virtual screening, cheminformatics & QSAR. The Scientific Vector Language (SVL) is the built-in command, scripting and application development language of MOE.
LeDock is molecular docking software designed for ligand-protein interactions, compatible with Linux, macOS, and Windows. It supports the Tripos Mol2 file format and employs a simulated annealing and genetic algorithm approach for docking. Utilizing a knowledge-based scoring scheme, it is categorized as a flexible docking method.
FlexAID is a molecular docking software that can use small molecules and peptides as ligands and proteins and nucleic acids as docking targets. As the name suggests, FlexAID supports full ligand flexibility as well side-chain flexibility of the target. It does using a soft scoring function based on the complementarity of the two surfaces.
rDock is an open-source molecular docking software that be used for docking small molecules against proteins and nucleic acids. It is primarily designed for high-throughput virtual screening and prediction of binding mode.
Zhiping Weng is the Li Weibo Professor of biomedical research and chair of the program in integrative biology and bioinformatics at the University of Massachusetts Medical School. She was awarded Fellowship of the International Society for Computational Biology (ISCB) in 2020 for outstanding contributions to computational biology and bioinformatics.
