Prospects of Modulating Protein–Protein Interactions

Zhong, Shijun; Oashi, Taiji; Yu, Wenbo; Shapiro, Paul; MacKerell, Alexander D.

doi:10.1002/9783527645947.ch15

Cited by 5 publications

(6 citation statements)

References 238 publications

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“…Pharmacophore modeling is a widely used computer-aided drug design (CADD) approach that, in addition to docking methods, is used in virtual screening (VS) studies 1, 2 . Compared to the energy function driven docking methods, it is based on the pattern of functional groups that are crucial for interactions of ligands with the protein target.…”

Section: Introductionmentioning

confidence: 99%

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

Lakkaraju

Raman

et al. 2015

J. Chem. Inf. Model.

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Receptor-based pharmacophore modeling is an efficient computer-aided drug design technique that uses the structure of the target protein to identify novel leads. However, most methods consider protein flexibility and desolvation effects in a very approximate way, which may limit their use in practice. The Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling protocol (SILCS-Pharm) was introduced recently to address these issues as SILCS naturally takes both protein flexibility and desolvation effects into account by using full MD simulations to determine 3D maps of the functional group-affinity patterns on a target receptor. In the present work, the SILCS-Pharm protocol is extended to use a wider range of probe molecules including benzene, propane, methanol, formamide, acetaldehyde, methylammonium, acetate and water. This approach removes the previous ambiguity brought by using water as both the hydrogen-bond donor and acceptor probe molecule. The new SILCS-Pharm protocol is shown to yield improved screening results as compared to the previous approach based on three target proteins. Further validation of the new protocol using five additional protein targets showed improved screening compared to those using common docking methods, further indicating improvements brought by the explicit inclusion of additional feature types associated with the wider collection of probe molecules in the SILCS simulations. The advantage of using complementary features and volume constraints, based on exclusion maps of the protein defined from the SILCS simulations, is presented. In addition, re-ranking using SILCS-based ligand grid free energies is shown to enhance the diversity of identified ligands for the majority of targets. These results suggest that the SILCS-Pharm protocol will be of utility in rational drug design.

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Section: Introductionmentioning

confidence: 99%

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

Lakkaraju

Raman

et al. 2015

J. Chem. Inf. Model.

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“…[1,2] Once the disease related biological pathway and a potential target in that pathway, including the structure of the target, is known, structure-based drug design (SBDD) methods can be used to facilitate the drug design process. Based on the target structure, either force field based energetic descriptions of the target or interaction patterns of specific chemical types with the target can be explored and high-throughput virtual screening (VS) may be performed against a large chemical compound database to identify potential novel lead compounds.…”

Section: Introductionmentioning

confidence: 99%

Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling

Lakkaraju

Raman

et al. 2014

J Comput Aided Mol Des

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Database screening using receptor-based pharmacophores is a computer-aided drug design technique that uses the structure of the target molecule (i.e. protein) to identify novel ligands that may bind to the target. Typically receptor-based pharmacophore modeling methods only consider a single or limited number of receptor conformations and map out the favorable binding patterns in vacuum or with a limited representation of the aqueous solvent environment, such that they may suffer from neglect of protein flexibility and desolvation effects. Site-Identification by Ligand Competitive Saturation (SILCS) is an approach that takes into account these, as well as other, properties to determine 3-dimensional maps of the functional group-binding patterns on a target receptor (i.e. FragMaps). In this study, a method to use the FragMaps to automatically generate receptor-based pharmacophore models is presented. It converts the FragMaps into SILCS pharmacophore features including aromatic, aliphatic, hydrogen-bond donor and acceptor chemical functionalities. The method generates multiple pharmacophore hypotheses that are then quantitatively ranked using SILCS grid free energies. The pharmacophore model generation protocol is validated using three different protein targets, including using the resulting models in virtual screening. Improved performance and efficiency of the SILCS derived pharmacophore models as compared to published docking studies, as well as a recently developed receptor-based pharmacophore modeling method is shown, indicating the potential utility of the approach in rational drug design.

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“…Compounds are then ranked based on their interactions energies and selected for further analyses. It is suggested that multiple step VS can be used to balance the efficiency and reliability of docking results (79, 80). This approach applies a more approximate, computationally faster approach for the full database of typically > 1 million compounds from which a subset of compounds are selected for a secondary, more accurate dock screen.…”

Section: Methodsmentioning

confidence: 99%

“…The fingerprint of a molecule refers to a collection of descriptors such as structural, physical, or chemical properties that are used to define the molecule (79). Structural fingerprints, for example BIT MACCS (89) encodes information such as the presence of specific types of atoms, bonds, or rings in the molecule and can be used to identify compounds that are structurally similar to the lead, facilitating SAR development, and may have improved binding affinity (88).…”

Section: Methodsmentioning

confidence: 99%

Computer-Aided Drug Design Methods

MacKerell

2016

Methods in Molecular Biology

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237

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Computational approaches are useful tools to interpret and guide experiments to expedite the antibiotic drug design process. Structure based drug design (SBDD) and ligand based drug design (LBDD) are the two general types of computer-aided drug design (CADD) approaches in existence. SBDD methods analyze macromolecular target 3-dimensional structural information, typically of proteins or RNA, to identify key sites and interactions that are important for their respective biological functions. Such information can then be utilized to design antibiotic drugs that can compete with essential interactions involving the target and thus interrupt the biological pathways essential for survival of the microorganism(s). LBDD methods focus on known antibiotic ligands for a target to establish a relationship between their physiochemical properties and antibiotic activities, referred to as a structure-activity relationship (SAR), information that can be used for optimization of known drugs or guide the design of new drugs with improved activity. In this chapter, standard CADD protocols for both SBDD and LBDD will be presented with a special focus on methodologies and targets routinely studied in our laboratory for antibiotic drug discoveries.

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Prospects of Modulating Protein–Protein Interactions

Cited by 5 publications

References 238 publications

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

Pharmacophore Modeling Using Site-Identification by Ligand Competitive Saturation (SILCS) with Multiple Probe Molecules

Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling

Computer-Aided Drug Design Methods

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