In Silico Structure-Based Prediction
of Receptor–Ligand Binding Affinity:
Current Progress and Challenges
Shailesh Kumar Panday and Indira Ghosh
Abstract Structure-based in silico studies aiming to predict affinity of a set of
ligands to their cognate receptor have been enjoying keen interest and attention of
researchers in drug design around the globe since many decades, and made significant progress to increase its predictive power, even it has emerged as a complementary field to in vivo and in vitro studies in recent years. Structure-based drug
discovery (SBDD) process whose success heavily relies on a careful selection of
structure of receptor and ligands and its accuracy, completeness, and rigor of
chosen model, imitation of the physiological condition in such in silico models,
e.g., pH and solvation. Appropriateness of selected mechanism of binding concept
and the realization in mathematical terms used in scoring methods have a strong
influence on the accuracy too. However, constant identification of new targets using
systems approach like genomics, proteomics, metabolomics, and network biology
has led a paradigm shift from single or a couple of targets toward the appreciation
of emerging role of a network of targets. The application of such strategies in study
of complex diseases is gaining attention. Identification of binding sites of receptor
and their characterization is important to be able to portray its interacting features. It
involves the search of ligands which are able to possess the features, present them
complementary to the binding site, so by docking the set of ligands to the binding
pocket of the receptor, activity can be evaluated. In silico receptor–ligand binding
affinity prediction from docking has witnessed rigid-receptor rigid-ligand to
flexible-ligand rigid-receptor treatment, and nowadays docking studies, through
sampling side chain rotations of the binding site residues, also account for the
flexibility of binding pocket of the receptor in indirect way. Literature survey has
shown progress in ranking ligands in order of affinity using reliable scoring functions to find potent scaffolds which can be further optimized to gain more affinity.
Many methods include effect of solvation in binding processes, like considering
conserved water positions in active sites (water maps), explicit water simulation in
presence of ligand with receptor, free energy perturbation, and thermodynamic
S. K. Panday Á I. Ghosh (&)
School of Computational and Integrative Sciences (SCIS),
Jawaharlal Nehru University, New Delhi 110067, India
e-mail: indira0654@gmail.com
© Springer Nature Switzerland AG 2019
C. G. Mohan (ed.), Structural Bioinformatics: Applications in Preclinical Drug
Discovery Process, Challenges and Advances in Computational Chemistry
and Physics 27, https://doi.org/10.1007/978-3-030-05282-9_5
109
of Receptor–Ligand Binding Affinity:
Current Progress and Challenges
Shailesh Kumar Panday and Indira Ghosh
Abstract Structure-based in silico studies aiming to predict affinity of a set of
ligands to their cognate receptor have been enjoying keen interest and attention of
researchers in drug design around the globe since many decades, and made significant progress to increase its predictive power, even it has emerged as a complementary field to in vivo and in vitro studies in recent years. Structure-based drug
discovery (SBDD) process whose success heavily relies on a careful selection of
structure of receptor and ligands and its accuracy, completeness, and rigor of
chosen model, imitation of the physiological condition in such in silico models,
e.g., pH and solvation. Appropriateness of selected mechanism of binding concept
and the realization in mathematical terms used in scoring methods have a strong
influence on the accuracy too. However, constant identification of new targets using
systems approach like genomics, proteomics, metabolomics, and network biology
has led a paradigm shift from single or a couple of targets toward the appreciation
of emerging role of a network of targets. The application of such strategies in study
of complex diseases is gaining attention. Identification of binding sites of receptor
and their characterization is important to be able to portray its interacting features. It
involves the search of ligands which are able to possess the features, present them
complementary to the binding site, so by docking the set of ligands to the binding
pocket of the receptor, activity can be evaluated. In silico receptor–ligand binding
affinity prediction from docking has witnessed rigid-receptor rigid-ligand to
flexible-ligand rigid-receptor treatment, and nowadays docking studies, through
sampling side chain rotations of the binding site residues, also account for the
flexibility of binding pocket of the receptor in indirect way. Literature survey has
shown progress in ranking ligands in order of affinity using reliable scoring functions to find potent scaffolds which can be further optimized to gain more affinity.
Many methods include effect of solvation in binding processes, like considering
conserved water positions in active sites (water maps), explicit water simulation in
presence of ligand with receptor, free energy perturbation, and thermodynamic
S. K. Panday Á I. Ghosh (&)
School of Computational and Integrative Sciences (SCIS),
Jawaharlal Nehru University, New Delhi 110067, India
e-mail: indira0654@gmail.com
© Springer Nature Switzerland AG 2019
C. G. Mohan (ed.), Structural Bioinformatics: Applications in Preclinical Drug
Discovery Process, Challenges and Advances in Computational Chemistry
and Physics 27, https://doi.org/10.1007/978-3-030-05282-9_5
109