Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR.

Binding of the Tat protein to TAR RNA is necessary for viral replication of HIV-1. We screened the Available Chemicals Directory (ACD) to identify ligands to bind to a TAR RNA structure using a four-step docking procedure: rigid docking first, followed by three steps of flexible docking using a pseudobrownian Monte Carlo minimization in torsion angle space with progressively more detailed conformational sampling on a progressively smaller list of top-ranking compounds. To validate the procedure, we successfully docked ligands for five RNA complexes of known structure. For ranking ligands according to binding avidity, an empirical binding free energy function was developed which accounts, in particular, for solvation, isomerization free energy, and changes in conformational entropy. System-specific parameters for the function were derived on a training set of RNA/ligand complexes with known structure and affinity. To validate the free energy function, we screened the entire ACD for ligands for an RNA aptamer which binds L-arginine tightly. The native ligand ranked 17 out of ca. 153,000 compounds screened, i.e., the procedure is able to filter out >99.98% of the database and still retain the native ligand. Screening of the ACD for TAR ligands yielded a high rank for all known TAR ligands contained in the ACD and suggested several other potential TAR ligands. Eight of the highest ranking compounds not previously known to be ligands were assayed for inhibition of the Tat-TAR interaction, and two exhibited a CD50 of ca. 1 microM.

Three-dimensional RNA structure-based drug discovery.

Abstract We have initiated a program to develop promising drug candidate leads using a new drug discovery paradigm based on three-dimensional RNA-structure-based computational screening of about 200,000 commercially available compounds for binding to selected RNA targets. As our first endeavor, we are using the three-dimensional structure of portions of the HIV-1 genome. Candidate lead compounds we seek are water-soluble, nonpeptide, nonnucleotide organic compounds generally with molecular weight less than 500 daltons. Structural studies of complexes formed with potential leads and their RNA targets should eventually yield insight into features governing affinity and specificity. The promising leads identified by virtual screening are tested for inhibition in functional assays. Leads will be selected for further development via computational and experimental combinatorial chemistry.

Structure-based design of ligands for protein basic domains: application to the HIV-1 Tat protein.

A methodology has been developed for designing ligands to bind a flexible basic protein domain where the structure of the domain is essentially known. It is based on an empirical binding free energy function developed for highly charged complexes and on Monte Carlo simulations in internal coordinates with both the ligand and the receptor being flexible. HIV-1 encodes a transactivating regulatory protein called Tat. Binding of the basic domain of Tat to TAR RNA is required for efficient transcription of the viral genome. The structure of a biologically active peptide containing the Tat basic RNA-binding domain is available from NMR studies. The goal of the current project is to design a ligand which will bind to that basic domain and potentially inhibit the TAR-Tat interaction. The basic domain contains six arginine and two lysine residues. Our strategy was to design a ligand for arginine first and then a superligand for the basic domain by joining arginine ligands with a linker. Several possible arginine ligands were obtained by searching the Available Chemicals Directory with DOCK 3.5 software. Phytic acid, which can potentially bind multiple arginines, was chosen as a building block for the superligand. Calormetric binding studies of several compounds to methylguanidine and Arg-/Lys-containing peptides were performed. The data were used to develop an empirical binding free energy function for prediction of affinity of the ligands for the Tat basic domain. Modeling of the conformations of the complexes with both the superligand and the basic domain being flexible has been carried out via Biased Probability Monte Carlo (BPMC) simulations in internal coordinates (ICM 2.6 suite of programs). The simulations used parameters to ensure correct folding, i.e., consistent with the experimental NMR structure of a 25-residue Tat peptide, from a random starting conformation. Superligands for the basic domain were designed by joining together two molecules of phytic acid with peptidic and peptidomimetic linkers. The linkers were refined by varying the length and side chains of the linking residues, carrying out BPMC simulations, and evaluation of the binding free energy for the best energy conformation. The dissociation constant of the best ligand designed is estimated to be in the low- to mid-nanomolar range.