A toolkit for covalent docking with GOLD: from automated ligand preparation with KNIME to bound protein-ligand complexes.

Motivation: Current covalent docking tools have limitations that make them difficult to use for performing large-scale structure-based covalent virtual screening (VS). They require time-consuming tasks for the preparation of proteins and compounds (standardization, filtering according to the type of warheads), as well as for setting up covalent reactions. We have developed a toolkit to help accelerate drug discovery projects in the phases of hit identification by VS of ultra-large covalent libraries and hit expansion by exploration of the binding of known covalent compounds. With this application note, we offer the community a toolkit for performing automated covalent docking in a fast and efficient way. Results: The toolkit comprises a KNIME workflow for ligand preparation and a Python program to perform the covalent docking of ligands with the GOLD docking engine running in a parallelized fashion. Availability and implementation: The KNIME workflow entitled 'Evotec_Covalent_Processing_forGOLD.knwf' for the preparation of the ligands is available in the KNIME Hub https://hub.knime.com/emilie_pihan/spaces. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Modeling and Deorphanization of Orphan GPCRs.

Despite tremendous efforts, approximately 120 GPCRs remain orphan. Their physiological functions and their potential roles in diseases are poorly understood. Orphan GPCRs are extremely important because they may provide novel therapeutic targets for unmet medical needs. As a complement to experimental approaches, molecular modeling and virtual screening are efficient techniques to discover synthetic surrogate ligands which can help to elucidate the role of oGPCRs. Constitutively activated mutants and recently published active structures of GPCRs provide stimulating opportunities for building active molecular models for oGPCRs and identifying activators using virtual screening of compound libraries. We describe the molecular modeling and virtual screening process we have applied in the discovery of surrogate ligands, and provide examples for CCKA, a simulated oGPCR, and for two oGPCRs, GPR52 and GPR34.

Virtual screening on an α-helix to ß-strand switchable region of the FGFR2 extracellular domain revealed positive and negative modulators.

The secondary structure of some protein segments may vary between α-helix and ß-strand. To predict these switchable segments, we have developed an algorithm, Switch-P, based solely on the protein sequence. This algorithm was used on the extracellular parts of FGF receptors. For FGFR2, it predicted that ß4 and ß5 strands of the third Ig-like domain were highly switchable. These two strands possess a high number of somatic mutations associated with cancer. Analysis of PDB structures of FGF receptors confirmed the switchability prediction for ß5. We thus evaluated if compound-driven α-helix/ß-strand switching of ß5 could modulate FGFR2 signaling. We performed the virtual screening of a library containing 1.4 million of chemical compounds with two models of the third Ig-like domain of FGFR2 showing different secondary structures for ß5, and we selected 32 compounds. Experimental testing using proliferation assays with FGF7-stimulated SNU-16 cells and a FGFR2-dependent Erk1/2 phosphorylation assay with FGFR2-transfected L6 cells, revealed activators and inhibitors of FGFR2. Our method for the identification of switchable proteinic regions, associated with our virtual screening approach, provides an opportunity to discover new generation of drugs with under-explored mechanism of action.

Targeting the TLR co-receptor CD14 with TLR2-derived peptides modulates immune responses to pathogens.

Dysregulation of Toll-like receptor (TLR) responses to pathogens can lead to pathological inflammation or to immune hyporesponsiveness and susceptibility to infections, and may affect adaptive immune responses. TLRs are therefore attractive therapeutic targets. We assessed the potential of the TLR co-receptor CD14 as a target for therapeutics by investigating the magnitude of its influence on TLR responses. We studied the interaction of CD14 with TLR2 by conducting peptide screening and site-directed mutagenesis analysis and found TLR2 leucine-rich repeats 5, 9, 15, and 20 involved in interaction with CD14. Peptides representing these regions interacted with CD14 and enhanced TLR2- and TLR4-mediated proinflammatory responses to bacterial pathogens in vitro. Notably, the peptides' immune boosting capacity helped to rescue proinflammatory responses of immunosuppressed sepsis patients ex vivo. In vivo, peptide treatment increased phagocyte recruitment and accelerated bacterial clearance in murine models of Gram-negative and Gram-positive bacterial peritonitis. Up-modulating CD14's co-receptor activity with TLR2-derived peptides also enhanced antigen-induced dendritic cell (DC) maturation and interleukin-2 production and, most notably, differentially affected DC cytokine profile upon antigen stimulation, promoting a T helper 1-skewed adaptive immune response. Biochemical, cell imaging, and molecular docking studies showed that peptide binding to CD14 accelerates microbial ligand transfer from CD14 to TLR2, resulting in increased and sustained ligand occupancy of TLR2 and receptor clustering for signaling. These findings reveal the influence that CD14 exerts on TLR activities and describe a potential therapeutic strategy to amplify responses to different pathogens mediated by different TLRs by targeting the common TLR co-receptor, CD14.

A Strategy Combining Differential Low-Throughput Screening and Virtual Screening (DLS-VS) Accelerating the Discovery of new Modulators for the Orphan GPR34 Receptor.

The DLS-VS strategy was developed as an integrated method for identifying chemical modulators for orphan GPCRs. It combines differential low-throughput screening (DLS) and virtual screening (VS). The two cascaded techniques offer complementary advantages and allow the experimental testing of a minimal number of compounds. First, DLS identifies modulators specific for the considered receptor among a set of receptors, through the screening of a small library with diverse chemical compounds. Then, an active molecular model of the receptor is built by homology to a validated template, and it is progressively refined by rotamers modification for key side-chains, by VS of the already screened library, and by iterative selection of the model generating the best enrichment. The refined active model is finally used for the VS of a large chemical library and the selection of a small set of compounds for experimental testing. Applied to the orphan receptor GPR34, the DLS-VS strategy combined the experimental screening of 20 000 compounds and the virtual screening of 1 250 000 compounds. It identified one agonist and eight inverse agonists, showing a high chemical diversity. We describe the method. The strategy can be applied to other GPCRs.

Differential Virtual Screening (DVS) with Active and Inactive Molecular Models for Finding and Profiling GPCR Modulators: Case of the CCK1 Receptor.

We discovered a constitutively activating mutation (CAM) V308E for the neurotensin NT1 receptor. Molecular dynamics (MD) performed for the CAM NT1-V308E exhibiting a high spontaneous activity, and for the wild-type NT1 without basal activity, show dramatic conformational changes for the CAM. To test if the two MD models could be valuable active and inactive templates for building molecular models for other class-A GPCR, supposed active and inactive models were built by homology for the cholecystokinin CCK1 receptor. Virtual screening of a corporate library with 250 000 compounds was performed with the two CCK1 models, and a differential virtual screening analysis (DVS), led us to isolate 250 predicted agonists and 250 predicted antagonists. The two sets were merged and the compounds were tested in CCK1 agonist and antagonist cellular assays. An excellent correlation was obtained between predictions and biological results. The effective profiling provided by DVS with active and inactive molecular models, opens new perspectives for finding agonists and antagonists for other class-A GPCR, notably for orphan GPCRs for which no ligands are known.

Toward the active conformations of rhodopsin and the beta2-adrenergic receptor.

Using sets of experimental distance restraints, which characterize active or inactive receptor conformations, and the X-ray crystal structure of the inactive form of bovine rhodopsin as a starting point, we have constructed models of both the active and inactive forms of rhodopsin and the beta2-adrenergic G-protein coupled receptors (GPCRs). The distance restraints were obtained from published data for site-directed crosslinking, engineered zinc binding, site-directed spin-labeling, IR spectroscopy, and cysteine accessibility studies conducted on class A GPCRs. Molecular dynamics simulations in the presence of either "active" or "inactive" restraints were used to generate two distinguishable receptor models. The process for generating the inactive and active models was validated by the hit rates, yields, and enrichment factors determined for the selection of antagonists in the inactive model and for the selection of agonists in the active model from a set of nonadrenergic GPCR drug-like ligands in a virtual screen using ligand docking software. The simulation results provide new insights into the relationships observed between selected biochemical data, the crystal structure of rhodopsin, and the structural rearrangements that occur during activation.