Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Structure-based virtual screening (VS) is a widely used approach that employs the knowledge of the three-dimensional structure of the target of interest in the design of new lead compounds from large-scale molecular docking experiments. Through the prediction of the binding mode and affinity of a small molecule within the binding site of the target of interest, it is possible to understand important properties related to the binding process. Empirical scoring functions are widely used for pose and affinity prediction. Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments. There are several efforts in distinct fronts to develop even more sophisticated and accurate models for filtering and ranking large libraries of compounds. This paper will cover some recent successful applications and methodological advances, including strategies to explore the ligand entropy and solvent effects, training with sophisticated machine-learning techniques, and the use of quantum mechanics. Particular emphasis will be given to the discussion of critical aspects and further directions for the development of more accurate empirical scoring functions

The Development and Applications of the HINT Scoring Function: Exploring Colchicine-Site Anticancer Agents and Tautomerism

The overall aim of this work was to apply HINT, an empirical scoring function based on the understanding of hydrophobicity, to analyze and predict the binding affinities and biological activities of colchicine-site anticancer agents. The second, concurrent aim was to improve the scoring function by incorporating tautomerism within the modeling process. Our belief is that proper evaluation of tautomeric forms for small molecules will improve performance of virtual screening. The novel pyrrole-based compounds targeting the colchicine site were docked into the receptor using HINT as a rescoring function. Two distinct binding modes dictated by the size and shape of a subpocket were predicted to differentiate the highly active compounds from the weak ones. Of the residues predicted to participate in binding for the active binding mode, Cys241β was revealed to form a weak but critical hydrogen bond with the ligand. A larger collection of colchicine-site agents, biologically tested in the same laboratory including our pyrrole-based compounds were subject to 3D quantitative structure-activity relationship (QSAR) study. Using results on docking the pyrrole compounds as a guide, relative binding poses and QSAR models were built to facilitate ligand design and optimization. A new 3D modeling approach was introduced to visually highlight the unique features of highly active compounds and the commonality of all compounds in the dataset using HINT maps and successfully tested on the colchicine-site agents. These results will provide valuable guidance in the future design and development of new colchicine-site agents. To incorporate tautomerism within HINT, we proposed and developed two workflow approaches: a general search tool using a simple and intuitive algorithm analyzing hydrogen shift patterns to identify and enumerate tautomeric structures, and a database that contains commonly observed tautomeric structures. The first approach was designed for small-scale docking studies and the second approach was designed for large-scale virtual screening. The tautomer module in HINT will give more accurate modeling results when the compound encountered is able to tautomerize