In Silico End-to-End Protein-Ligand Interaction Characterization Pipeline: The Case of SARS-CoV-2.

SARS-CoV-2 triggered a worldwide pandemic disease, COVID-19, for which an effective treatment has not yet been settled. Among the most promising targets to fight this disease is SARS-CoV-2 main protease (Mpro), which has been extensively studied in the last few months. There is an urgency for developing effective computational protocols that can help us tackle these key viral proteins. Hence, we have put together a robust and thorough pipeline of in silico protein-ligand characterization methods to address one of the biggest biological problems currently plaguing our world. These methodologies were used to characterize the interaction of SARS-CoV-2 Mpro with an α-ketoamide inhibitor and include details on how to upload, visualize, and manage the three-dimensional structure of the complex and acquire high-quality figures for scientific publications using PyMOL (Protocol 1); perform homology modeling with MODELLER (Protocol 2); perform protein-ligand docking calculations using HADDOCK (Protocol 3); run a virtual screening protocol of a small compound database of SARS-CoV-2 candidate inhibitors with AutoDock 4 and AutoDock Vina (Protocol 4); and, finally, sample the conformational space at the atomic level between SARS-CoV-2 Mpro and the α-ketoamide inhibitor with Molecular Dynamics simulations using GROMACS (Protocol 5). Guidelines for careful data analysis and interpretation are also provided for each Protocol.

Decoding Partner Specificity of Opioid Receptor Family.

This paper describes an exciting big data analysis compiled in a freely available database, which can be applied to characterize the coupling of different G-Protein coupled receptors (GPCRs) families with their intracellular partners. Opioid receptor (OR) family was used as case study in order to gain further insights into the physiological properties of these important drug targets, known to be associated with the opioid crisis, a huge socio-economic issue directly related to drug abuse. An extensive characterization of all members of the ORs family (µ (MOR), δ (DOR), κ (KOR), nociceptin (NOP)) and their corresponding binding partners (ARRs: Arr2, Arr3; G-protein: Gi1, Gi2, Gi3, Go, Gob, Gz, Gq, G11, G14, G15, G12, Gssh, Gslo) was carried out. A multi-step approach including models' construction (multiple sequence alignment, homology modeling), complex assembling (protein complex refinement with HADDOCK and complex equilibration), and protein-protein interface characterization (including both structural and dynamics analysis) were performed. Our database can be easily applied to several GPCR sub-families, to determine the key structural and dynamical determinants involved in GPCR coupling selectivity.

Inhibition of α-glucosidase by flavonoids of Cymbopogon citratus (DC) Stapf.

ETHNOPHARMACOLOGICAL RELEVANCE: Leaves extracts from Cymbopogon citratus (DC) Stapf. are widely used in traditional medicine exhibiting several in vivo biological activities, including antidiabetic. Several flavonoids, including aglycones and glycosides, were reported in this plant and previous studies suggested that flavonoids may interact with targets related to diabetes. AIM OF THE STUDY: Evaluated the hypoglycemic activity of C. citratus flavonoids through α-glucosidase inhibition and assess the structure-activity relationship using molecular docking studies. MATERIAL AND METHODS: An infusion of C. citratus leaves and its flavonoid-rich fraction were prepared. Five flavonoids from this fraction were isolated and structurally characterized by UV spectral analysis with shift reagents, HPLC-PDA-ESI/MSn and 1H NMR. The antidiabetic potential of C. citratus infusion, its flavonoid-rich fraction, glycosylated flavonoids and aglycones was evaluated trough the in vitro inhibition of yeast α-glucosidase. Posteriorly, molecular docking of the tested flavonoids was performed to investigate its possible interactions with the α-glucosidase pocket. RESULTS: The infusion of C. citratus, its flavonoid-rich fraction, luteolin and five flavone glycosides namely, luteolin 6-C-ß-glucopyranoside (isoorientin), luteolin 7-O-neohesperidoside (ionicerin), luteolin 7-O-ß-glucopyranoside (cynaroside), Luteolin 2″-O-rhamnosyl-C-(6-deoxy-ribo-hexos-3-ulosyl) (cassiaoccidentalin B), luteolin 6-C-α-arabinofuranosil-(1→2)-α-L-rhamnopyranoside (kurilesin A) showed higher inhibitory activity than the reference drug. This activity increased by the addition of a sugar moiety. However, the di-glycosides were less active than mono-glycosides. The docking studies showed interactions of sugar moieties and A or B rings with the catalytic pocket mainly through hydrogen bonds. CONCLUSIONS: Our results corroborate the potential of C. citratus as a medicinal plant for the treatment of diabetes and revealed that its flavonoid glycosides has hypoglycemic effect and can be explored as drug candidates to act as α-glucosidase inhibitors in the treatment of diabetes.

Understanding the Binding Specificity of G-Protein Coupled Receptors toward G-Proteins and Arrestins: Application to the Dopamine Receptor Family.

G-Protein coupled receptors (GPCRs) are involved in a myriad of pathways key for human physiology through the formation of complexes with intracellular partners such as G-proteins and arrestins (Arrs). However, the structural and dynamical determinants of these complexes are still largely unknown. Herein, we developed a computational big-data pipeline that enables the structural characterization of GPCR complexes with no available structure. This pipeline was used to study a well-known group of catecholamine receptors, the human dopamine receptor (DXR) family and its complexes, producing novel insights into the physiological properties of these important drug targets. A detailed description of the protein interfaces of all members of the DXR family (D1R, D2R, D3R, D4R, and D5R) and the corresponding protein interfaces of their binding partners (Arrs: Arr2 and Arr3; G-proteins: Gi1, Gi2, Gi3, Go, Gob, Gq, Gslo, Gssh, Gt2, and Gz) was generated. To produce reliable structures of the DXR family in complex with either G-proteins or Arrs, we performed homology modeling using as templates the structures of the ß2-adrenergic receptor (ß2AR) bound to Gs, the rhodopsin bound to Gi, and the recently acquired neurotensin receptor-1 (NTSR1) and muscarinic 2 receptor (M2R) bound to arrestin (Arr). Among others, the work demonstrated that the three partner groups, Arrs and Gs- and Gi-proteins, are all structurally and dynamically distinct. Additionally, it was revealed the involvement of different structural motifs in G-protein selective coupling between D1- and D2-like receptors. Having constructed and analyzed 50 models involving DXR, this work represents an unprecedented large-scale analysis of GPCR-intracellular partner interface determinants. All data is available at www.moreiralab.com/resources/dxr.

New BACE1 Chimeric Peptide Inhibitors Selectively Prevent AßPP-ß Cleavage Decreasing Amyloid-ß Production and Accumulation in Alzheimer's Disease Models.

BACKGROUND: A disease-modifying therapy for Alzheimer's disease (AD) is still an unmet clinical need. The formation of amyloid-ß (Aß) requires the initial cleavage of the amyloid-ß protein precursor (AßPP) by BACE1 (beta-site AßPP cleaving enzyme 1), which is a prime therapeutic target for AD. OBJECTIVE: We aimed to design and develop a selective BACE1 inhibitor suitable to AD treatment. METHODS: The new BACE1 inhibitors consist on a chimeric peptide including a sequence related to the human Swedish mutant form of AßPP (AßPPswe) conjugated with the TAT carrier that facilitates cell membrane permeation and the crossing of the blood-brain barrier. Additionally to the chimeric peptide in the L-form, we developed a D-retroinverso chimeric peptide. The latter strategy, never used with BACE1 inhibitors, is considered to favor a significantly higher half-life and lower immunogenicity. RESULTS: We found that both chimeric peptides inhibit recombinant BACE1 activity and decrease Aß40/42 production in Neuro-2a (N2A) cells expressing AßPPswe without inducing cytotoxicity. The intraperitoneal administration of these peptides to 3xTg-AD mice decreased plasma and brain Aß40/42 levels, as well as brain soluble AßPPß production. Also, a reduction of insoluble Aß was observed in the brain after chronic treatment. Noteworthy, the chimeric peptides selectively inhibited the AßPP-ß cleavage relatively to the proteolysis of other BACE1 substrates such as close homologue of L1 (CHL1) and seizure-related gene 6 (SEZ6). CONCLUSIONS: Overall these new BACE1 chimeric peptideshold promising potential as a selective disease-modifying therapy for AD.

Combining Virtual Screening Protocol and In Vitro Evaluation towards the Discovery of BACE1 Inhibitors.

The treatment options for a patient diagnosed with Alzheimer's disease (AD) are currently limited. The cerebral accumulation of amyloid-ß (Aß) is a critical molecular event in the pathogenesis of AD. When the amyloidogenic ß-secretase (BACE1) is inhibited, the production of Aß peptide is reduced. Henceforth, the main goal of this study is the discovery of new small bioactive molecules that potentially reach the brain and inhibit BACE1. The work was conducted by a customized molecular modelling protocol, including pharmacophore-based and molecular docking-based virtual screening (VS). Structure-based (SB) and ligand-based (LB) pharmacophore models were designed to accurately screen several drug-like compound databases. The retrieved hits were subjected to molecular docking and in silico filtered to predict their ability to cross the blood-brain barrier (BBB). Additionally, 34 high-scoring compounds structurally distinct from known BACE1 inhibitors were selected for in vitro screening assay, which resulted in 13 novel hit-compounds for this relevant therapeutic target. This study disclosed new BACE1 inhibitors, proving the utility of combining computational and in vitro approaches for effectively predicting anti-BACE1 agents in the early drug discovery process.

Prediction and targeting of GPCR oligomer interfaces.

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.

Highlights in BACE1 Inhibitors for Alzheimer's Disease Treatment.

Alzheimer's disease (AD) is a severe neurodegenerative disorder and the most common type of dementia in the elderly. The clinical symptoms of AD include a progressive loss of memory and impairment of cognitive functions interfering with daily life activities. The main neuropathological features consist in extracellular amyloid-ß (Aß) plaque deposition and intracellular Neurofibrillary tangles (NFTs) of hyperphosphorylated Tau. Understanding the pathophysiological mechanisms that underlie neurodegeneration in AD is essential for rational design of neuroprotective agents able to prevent disease progression. According to the "Amyloid Cascade Hypothesis" the critical molecular event in the pathogenesis of AD is the accumulation of Aß neurotoxic oligomers. Since the proteolytic processing of Amyloid Precursor Protein (APP) by ß-secretase (beta-site APP cleaving enzyme 1, BACE1) is the rate-limiting step in the production of Aß, this enzyme is considered a major therapeutic target and BACE1 inhibitors have the potential to be disease-modifying drugs for AD treatment. Therefore, intensive efforts to discover and develop inhibitors that can reach the brain and effectively inhibit BACE1 have been pursued by several groups worldwide. The aim of this review is to highlight the progress in the discovery of potent and selective small molecule BACE1 inhibitors over the past decade.

Novel PARP-1 Inhibitor Scaffolds Disclosed by a Dynamic Structure-Based Pharmacophore Approach.

PARP-1 inhibition has been studied over the last decades for the treatment of various diseases. Despite the fact that several molecules act as PARP-1 inhibitors, a reduced number of compounds are used in clinical practice. To identify new compounds with a discriminatory PARP-1 inhibitory function, explicit-solvent molecular dynamics simulations using different inhibitors bound to the PARP-1 catalytic domain were performed. The representative structures obtained were used to generate structure-based pharmacophores, taking into account the dynamic features of receptor-ligand interactions. Thereafter, a virtual screening of compound databases using the pharmacophore models obtained was performed and the hits retrieved were subjected to molecular docking-based scoring. The drug-like molecules featuring the best ranking were evaluated for their PARP-1 inhibitory activity and IC50 values were calculated for the top scoring docked compounds. Altogether, three new PARP-1 inhibitor chemotypes were identified.