Molecular docking software is mainly used in drug development. offers a wide range of useful techniques for the creation and analysis pharmaceuticals. Before now, predicting target receptor was extremely challenging however, protein with ligand straightforward dependable procedure presently binding affinity designed. To see molecule's three-dimensional structure, variety tools have been created...

Crystallization of protein-protein complexes can often be problematic and therefore computational structural models are often relied on. Such models are often generated using protein-protein docking algorithms, where one of the main challenges is selecting which of several thousand potential predictions represents the most near-native complex. We have developed a novel technique that involves t...

acridine derivatives, especially 1,8-dioxo-9-aryl-decahydroacridine represent significant scaffolds in medicinal chemistry. given the biological properties of such products which are used in drug development, they need to have appropriate carrier. proteins are generally used as helpful tools in drug delivery. consequently, molecular docking between these compounds and bovine serum albumin (bsa)...

Molecular docking is a widely-used computational tool for the study of molecular recognition, which aims to predict the binding mode and binding affinity of a complex formed by two or more constituent molecules with known structures. An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the...

The idea in molecular docking is to design pharmaceuticals computationally by identifying potential drug candidates targeted against proteins. The candidates can be found using a docking algorithm that tries to identify the bound conformation of a small molecule ligand to a macromolecular target at its active site, which is the region of an enzyme where natural substrate binds. Mathematically, ...

objective(s): a fast and reliable evaluation of the binding energy from a single conformation of a molecular complex is an important practical task. artificial neural networks (anns) are strong tools for predicting nonlinear functions which are used in this paper to predict binding energy. we proposed a structure that obtains binding energy using physicochemical molecular descriptions of the se...

Tiagabine (Gabitril) is a selective inhibitor of the human gamma-aminobutyric acid (GABA) transporter 1 (hGAT-1), a transport protein belonging to the family of neurotransmitter-sodium-symporters (NSS). It is a marketed drug, used for treatment of epilepsy. However, the molecular basis of protein-ligand interaction remains obscure due to the lack of a 3D structure of the target protein. In orde...

The efficient and accurate quantification of protein-ligand interactions using computational methods is still a challenging task. Two factors strongly contribute to the failure of docking methods to predict free energies of binding accurately: the insufficient incorporation of protein flexibility coupled to ligand binding and the neglected dynamics of the protein-ligand complex in current scori...

Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in order to create a platform for arbitr...