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Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

Conserved Binding Sites

Conserved Binding Sites

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...

Ligand Binding and Linkage

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked. In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

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Updated: May 16, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

FINDSITE(comb): a threading/structure-based, proteomic-scale virtual ligand screening approach.

Hongyi Zhou¹, Jeffrey Skolnick

¹Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, 250 14th Street, N.W., Atlanta, Georgia 30318, USA.

Journal of Chemical Information and Modeling

|December 18, 2012

Summary

This summary is machine-generated.

A new FINDSITE(comb) method improves virtual ligand screening speed and accuracy. This approach effectively identifies potential drug candidates by analyzing protein structures and binding databases, making large-scale screening feasible.

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Last Updated: May 16, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Area of Science:

Computational chemistry
Drug discovery
Bioinformatics

Background:

Traditional virtual ligand screening methods have limitations.
Ligand-based screening requires diverse known ligands.
Structure-based screening needs high-resolution protein structures and is computationally intensive.

Purpose of the Study:

To develop an improved virtual ligand screening method.
To overcome limitations of traditional ligand- and structure-based approaches.
To enhance the accuracy and efficiency of drug discovery pipelines.

Main Methods:

Developed FINDSITE(filt) with improved binding site detection.
Combined FINDSITE(filt) with FINDSITE(X) using ChEMBL and DrugBank databases.
Compared FINDSITE(comb) to AUTODOCK Vina and DOCK 6 on the DUD benchmark set.

Main Results:

FINDSITE(comb) significantly outperformed traditional docking methods in enrichment factor, speed, and insensitivity to target structure quality.
Achieved average enrichment factors of 52.1 for generic targets and 22.3 for GPCRs.
Performance was robust with protein structures having a TM-score ≥ 0.4.

Conclusions:

FINDSITE(comb) enables feasible screening of millions of compounds across entire proteomes.
The method offers a faster, more accurate, and less resource-intensive alternative for virtual ligand screening.
A freely available web service facilitates academic use.