Binding Site Prediction
Binding Site Prediction - Related Videos
12:17
An In Vitro Caseum Binding Assay that Predicts Drug Penetration in Tuberculosis Lesions
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Cited by 24 •
2017
Here we describe a rapid equilibrium dialysis (RED) method to measure drug binding to caseum from pulmonary tuberculosis lesions and cavities. The protocol is also used with a foamy macrophage-derived matrix that is an effective surrogate to caseum.
01:49
Conserved Binding Sites
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2020
Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function. Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
02:18
The Equilibrium Binding Constant and Binding Strength
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2020
The equilibrium binding constant (Kb) quantifies the strength of a protein-ligand interaction. Kb can be calculated as follows when the reaction is at equilibrium: where P and L are the unbound protein and ligand, respectively, and PL is the protein-ligand complex. As the amount of bound ligand is also related to the rate of ligand binding, experiments can also determine Kb by examining the rates of protein-ligand association (kon) and dissociation (koff) using the following ratio: Thus,...
16:41
A Protocol for Computer-Based Protein Structure and Function Prediction
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Cited by 79 •
2011
Guidelines for computer based structural and functional characterization of protein using the I-TASSER pipeline is described. Starting from query protein sequence, 3D models are generated using multiple threading alignments and iterative structural assembly simulations. Functional inferences are thereafter drawn based on matches to proteins with known structure and functions.
02:27
Predicting Molecular Geometry
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2020
VSEPR Theory for Determination of Electron Pair Geometries The following procedure uses VSEPR theory to determine the electron pair geometries and the molecular structures: Write the Lewis structure of the molecule or polyatomic ion. Count the number of electron groups (lone pairs and bonds) around the central atom. A single, double, or triple bond counts as one region of electron density. Identify the electron-pair geometry based on the number of electron groups: linear, trigonal planar,...
FAQs
The method evaluates several complementary signals rather than relying on a single residue or surface property. Cavities and surface shape indicate whether a region can accommodate a partner, while electrostatic properties and hydrophobicity describe chemical compatibility. Residue conservation adds biological context, helping prioritize regions that may have remained important for molecular recognition or function.
Conservation can indicate that particular residues or regions have been maintained because they contribute to an important molecular role. When conserved residues coincide with suitable structural or chemical features, the region becomes a stronger candidate for interaction. Sequence-based evidence therefore complements structure-based analysis, especially when interpreting potential functional sites on proteins.
Molecular docking helps estimate how a ligand or other partner may fit within a proposed region and whether the local chemical environment appears compatible with that interaction. This adds an interaction-oriented assessment to the initial search for cavities, surfaces, or conserved regions. The resulting predictions can help compare plausible binding arrangements and guide targeted experiments.
Surface shape, cavity formation, electrostatic properties, hydrophobicity, and residue conservation provide different kinds of evidence. A region may appear geometrically accessible but lack suitable chemical characteristics, or show compatible chemistry without strong conservation. Considering these features together narrows a large molecular surface to regions that are more plausible for a specific interaction.
A typical workflow begins with sequence or structural information for the protein or other biomolecule and identifies candidate regions using surface geometry, cavities, electrostatics, hydrophobicity, and conservation. Molecular docking or sequence and structure-based models can then assess compatibility. Researchers use the prioritized regions to focus experimental testing instead of screening the entire molecular surface.
They can support protein function annotation by suggesting regions that may mediate interactions, and they can focus enzyme or receptor investigations on plausible ligand or substrate sites. In drug discovery, predicted regions help guide the search for compounds that could interact with a target. These uses make computational prioritization a practical complement to targeted biological experiments.
Predicted interaction regions can identify specific parts of a protein for closer investigation when researchers study binding by ligands, nucleic acids, or partner molecules. Testing those regions can clarify how molecular recognition contributes to cellular regulation. By concentrating experiments on computationally supported candidates, investigators can examine possible regulatory interactions without treating the entire biomolecule as equally informative.