Design of Ligand Binding to an Engineered Protein Cavity Using Virtual Screening and Thermal Up-shift Evaluation

Abstract

Proteins could be used to carry and deliver small compounds. As a tool for designing ligand binding sites in protein cores, a three-step virtual screening method is presented that has been optimised using existing data on T4 lysozyme complexes and tested in a newly engineered cavity in flavodoxin. The method can pinpoint, in large databases, ligands of specific protein cavities. In the first step, physico-chemical filters are used to screen the library and discard a majority of compounds. In the second step, a flexible, fast docking procedure is used to score and select a smaller number of compounds as potential binders. In the third step, a finer method is used to dock promising molecules of the hit list into the protein cavity, and an optimised free energy function allows discarding the few false positives by calculating the affinity of the modelled complexes. To demonstrate the portability of the method, several cavities have been designed and engineered in the flavodoxin from Anabaena PCC 7119, and the W66F/L44A double mutant has been selected as a suitable host protein. The NCI database has then been screened for potential binders, and the binding to the engineered cavity of five promising compounds and three tentative non-binders has been experimentally tested by thermal up-shift assays and spectroscopic titrations. The five tentative binders (some apolar and some polar), unlike the three tentative non-binders, are shown to bind to the host mutant and, importantly, not to bind to the wild type protein. The three-step virtual screening method developed can thus be used to identify ligands of buried protein cavities. We anticipate that the method could also be used, in a reverse manner, to identify natural or engineerable protein cavities for the hosting of ligands of interest.

Rescoring Docking Hit Lists for Model Cavity Sites: Predictions and Experimental Testing

“…21 Others have found them attractive test systems for method development studies. [31][32][33][34] An important advantage of these cavity sites is that they are experimentally tractable for detailed, prospective testing of ligand predictions. Because the ligands they bind are small-in the 70-to 150-amu range-many possible ligands are readily available commercially, which is rarely true of drug targets.…”

Docking-Based Virtual Screening: Recent Developments

“…Machicado and co-workers reported that prior to docking screening, the pre-selection of compounds was developed on the basis of volume and polarity characteristics [142], Barreiro and co-workers used a chemical similarity search [143,144], and Hu and co-workers discovered new Yersinia protein kinase A inhibitors by applying, prior to the docking studies, a machine-learning support vector machine model for obtaining a target-focused library beginning with a large chemical database [145].…”

Molecular Recognition and Drug-Lead Identification: What Can Molecular Simulations Tell Us?

“…Hence, to overcome this problem and to preserve some accuracy, several research groups have recently developed hierarchical methods that combine different strategies, using less accurate and faster approaches for preliminary screenings and higher-level of theory and expansive strategies for later stages. Machicado et al [106] proposed a three-step virtual screening strategy that enables to identify active ligands for buried protein cavities. It consists in applying some physicochemical filters, a fast docking procedure and, at the final stage, a finer flexible docking algorithm that exploits a Monte Carlo search technique and that uses a purposely defined binding free energy function to properly score the docked complexes.…”