Binding Site Volume Research Articles

In silico investigation of riboswitches in fungi: structural and dynamical insights into TPP riboswitches in Aspergillus oryzae

ABSTRACT Riboswitches are RNA sensors affecting post-transcriptional processes through their ability to bind to small molecules. Thiamine pyrophosphate (TPP) riboswitch plays a crucial role in regulating genes involved in synthesizing or transporting thiamine and phosphorylated derivatives in bacteria, archaea, plants, and fungi. Although TPP riboswitch is reasonably well known in bacteria, there is a gap in the knowledge of the fungal TPP riboswitches structure and dynamics, involving mainly sequence variation and TPP interaction with the aptamers. On the other hand, the increase of fungal infections and antifungal resistance raises the need for new antifungal therapies. In this work, we used computational approaches to build three-dimensional models for the three TPP riboswitches identified in Aspergillus oryzae, in which we studied their structure, dynamics, and binding free energy change (ΔGbind) with TPP. Interaction patterns between the TPP and the surrounding nucleotides were conserved among the three models, evidencing high structural conservation. Furthermore, we show that the TPP riboswitch from the A. oryzae NMT1 gene behaves similarly to the E. coli thiA gene concerning the ΔGbind. In contrast, mutations in the fungal TPP riboswitches from THI4 and the nucleoside transporter genes led to structural differences, affecting the binding-site volume, hydrogen bond occupancy, and ΔGbind. Besides, the number of water molecules surrounding TPP influenced the ΔGbind considerably. Notably, our ΔGbind estimation agreed with previous experimental data, reinforcing the relationship between sequence conservation and TPP interaction.

Identification of potential Leishmania chagasi superoxide dismutase allosteric modulators by structure-based computational approaches: homology modelling, molecular dynamics and pharmacophore-based virtual screening

The visceral form of Leishmaniasis, also known as kala-azar, caused by Leishmania chagasi is the main etiological agent of this form in Brazil responsible for 30,000 annual deaths. Despite its epidemiological impact, treatment of the disease is limited by resistance, species-dependent efficacy and serious adverse effects. The application of computational tools to prioritize potential bioactive molecules based on 3D structural of biological target is a viable alternative. Among the L. chagasi validated targets, Fe + 2 superoxide dismutase B2 (LcFeSODB2) is the first parasite enzyme against oxidative stress and it is involved in essential metabolic processes for its survival. Due to substrate binding-site volume (superoxide ion) and consequent difficulty in its active site modulation for small molecules, the search for allosteric sites at LcFeSODB2 3D structure is a promising strategy. As there are no 3D structures of LcFeSODB2, comparative modeling was applied to build 3D models by SWISS-MODEL and MODELLER version 9.19. Next, the best 3D model was used in molecular dynamics (MD) routines with multiple probes on GROMACS version 5.1.2. In addition, potential allosteric sites predicted by FTMap and Metapocket web servers were used with probe occupancy maps from MD to select an allosteric binding site and propose a pharmacophore model. Next, it was used as a template in virtual screening by UNITY® module available on SYBYL-X version 2.1.1 at Sigma-Aldrich CPR™ subset of ZINC12 database. The pharmacophore-based virtual screening resulted in the selection of two potential allosteric LcFeSOD compounds with partial pharmacophoric requirements, drug-like properties and commercial availability for enzymatic assays. Communicated by Ramaswamy H. Sarma

Binding Free Energies of Host-Guest Systems by Nonequilibrium Alchemical Simulations with Constrained Dynamics: Theoretical Framework.

The fast-switching decoupling method is a powerful nonequilibrium technique to compute absolute binding free energies of ligand-receptor complexes (Sandberg et al., J. Chem. Theory Comput. 2014, 11, 423-435). Inspired by the theory of noncovalent binding association of Gilson and co-workers (Biophys. J. 1997, 72, 1047-1069), we develop two approaches, termed binded-domain and single-point alchemical-path schemes (BiD-AP and SiP-AP), based on the possibility of performing alchemical trajectories during which the ligand is constrained to fixed positions relative to the receptor. The BiD-AP scheme exploits a recent generalization of nonequilibrium work theorems to estimate the free energy difference between the coupled and uncoupled states of the ligand-receptor complex. With respect to the fast-switching decoupling method without constraints, BiD-AP prevents the ligand from leaving the binding site, but still requires an estimate of the positional binding-site volume, which may not be a simple task. On the other side, the SiP-AP scheme allows avoidance of the calculation of the binding-site volume by introducing an additional equilibrium simulation of ligand and receptor in the bound state. In the companion article (DOI: 10.1021/acs.jctc.7b00595), we show that the extra computational effort required by SiP-AP leads to a significant improvement of accuracy in the free energy estimates.

Evaluation of the utility of homology models in high throughput docking

High throughput docking (HTD) is routinely used for in silico screening of compound libraries with the aim to find novel leads in a drug discovery program. In the absence of an experimentally determined structure, a homology model can be used instead. Here we present an assessment of the utility of homology models in HTD by docking 300,000 anticipated inactive compounds along with 642 known actives into the binding site of the insulin-like growth factor 1 receptor (IGF-1R) kinase constructed by homology modeling. Twenty-one different templates were selected and the enrichment curves obtained by the homology models were compared to those obtained by three IGF-1R crystal structures. The results show a wide range of enrichments from random to as good as two of the three IGF-1R crystal structures. Nevertheless, if we consider the enrichment obtained at 2% of the database screened as a performance criterion, the best crystal structure outperforms the best homology model. Surprisingly, the sequence identity of the template to the target is not a good descriptor to predict the enrichment obtained by a homology model. The three homology models that yield the worst enrichment have the smallest binding-site volume. Based on our results, we propose ensemble docking to perform HTD with homology models.