AI-Driven Discovery of SARS-CoV-2 Main Protease Fragment-like Inhibitors with Antiviral Activity In Vitro.

SARS-CoV-2 is the causative agent of COVID-19 and is responsible for the current global pandemic. The viral genome contains 5 major open reading frames of which the largest ORF1ab codes for two polyproteins, pp1ab and pp1a, which are subsequently cleaved into 16 nonstructural proteins (nsp) by two viral cysteine proteases encoded within the polyproteins. The main protease (Mpro, nsp5) cleaves the majority of the nsp's, making it essential for viral replication and has been successfully targeted for the development of antivirals. The first oral Mpro inhibitor, nirmatrelvir, was approved for treatment of COVID-19 in late December 2021 in combination with ritonavir as Paxlovid. Increasing the arsenal of antivirals and development of protease inhibitors and other antivirals with a varied mode of action remains a priority to reduce the likelihood for resistance emerging. Here, we report results from an artificial intelligence-driven approach followed by in vitro validation, allowing the identification of five fragment-like Mpro inhibitors with IC50 values ranging from 1.5 to 241 µM. The three most potent molecules (compounds 818, 737, and 183) were tested against SARS-CoV-2 by in vitro replication in Vero E6 and Calu-3 cells. Compound 818 was active in both cell models with an EC50 value comparable to its measured IC50 value. On the other hand, compounds 737 and 183 were only active in Calu-3, a preclinical model of respiratory cells, showing selective indexes twice as high as those for compound 818. We also show that our in silico methodology was successful in identifying both reversible and covalent inhibitors. For instance, compound 818 is a reversible chloromethylamide analogue of 8-methyl-γ-carboline, while compound 737 is an N-pyridyl-isatin that covalently inhibits Mpro. Given the small molecular weights of these fragments, their high binding efficiency in vitro and efficacy in blocking viral replication, these compounds represent good starting points for the development of potent lead molecules targeting the Mpro of SARS-CoV-2.

Discovery of new Schistosoma mansoni aspartyl protease inhibitors by structure-based virtual screening.

BACKGROUND: Schistosomiasis is a neglected tropical disease caused by trematodes of the genus Schistosoma, with a limited treatment, mainly based on the use of praziquantel (PZQ). Currently, several aspartic proteases genes have already been identified within the genome of Schistosoma species. At least one enzyme encoded from this gene family (SmAP), named SmCD1, has been validated for the development of schistosomicidal drugs, since it has a key role in haemoglobin digestion by worms. OBJECTIVE: In this work, we integrated a structure-based virtual screening campaign, enzymatic assays and adult worms ex vivo experiments aiming to discover the first classes of SmCD1 inhibitors. METHODS: Initially, the 3D-structures of SmCD1, SmCD2 and SmCD3 were generated using homology modelling approach. Using these models, we prioritised 50 compounds from 20,000 compounds from ChemBridge database for further testing in adult worm aqueous extract (AWAE) and recombinant SmCD1 using enzymatic assays. FINDINGS: Seven compounds were confirmed as hits and among them, two compounds representing new chemical scaffolds, named 5 and 19, had IC50 values against SmCD1 close to 100 µM while presenting binding efficiency indexes comparable to or even higher than pepstatin, a classical tight-binding peptide inhibitor of aspartyl proteases. Upon activity comparison against mammalian enzymes, compound 50 was selective and the most potent against the AWAE aspartic protease activity (IC50 = 77.7 µM). Combination of computational and experimental results indicate that compound 50 is a selective inhibitor of SmCD2. Compounds 5, 19 and 50 tested at low concentrations (10 uM) were neither cytotoxic against WSS-1 cells (48 h) nor could kill adult worms ex-vivo, although compounds 5 and 50 presented a slight decrease on female worms motility on late incubations times (48 or 72 h). MAIN CONCLUSION: Overall, the inhibitors identified in this work represent promising hits for further hit-to-lead optimisation.

COVID-19: molecular targets, drug repurposing and new avenues for drug discovery.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious infection that may break the healthcare system of several countries. Here, we aimed at presenting a critical view of ongoing drug repurposing efforts for COVID-19 as well as discussing opportunities for development of new treatments based on current knowledge of the mechanism of infection and potential targets within. Finally, we also discuss patent protection issues, cost effectiveness and scalability of synthetic routes for some of the most studied repurposing candidates since these are key aspects to meet global demand for COVID-19 treatment.

Compound profiling and 3D-QSAR studies of hydrazone derivatives with activity against intracellular Trypanosoma cruzi.

Chagas disease is a tropical disease caused by the parasite Trypanosoma cruzi, which is endemic in Central and South America. Few treatments are available with effectiveness limited to the early (acute) stage of disease, significant toxicity and widespread drug resistance. In this work we report the outcome of a HTS-ready assay chemical library screen to identify novel, nontoxic, small-molecule inhibitors of T. cruzi. We have selected 50 compounds that possess hydrazone as a common group. The compounds were screened using recombinant T. cruzi (Tulahuen strain) expressing beta-galactosidase. A 3D quantitative structure-activity relationship (QSAR) analysis was performed using descriptors calculated from comparative molecular field analysis (CoMFA). Our findings show that of the fifty selected hydrazones, compounds LpQM-19, 28 and 31 displayed the highest activity against T. cruzi, leading to a selectivity index (SI) of 20-fold. The 3D-QSAR analysis indicates that a particular electrostatic arrangement, where electron-deficient atoms are aligned along the molecule main axis positively correlates with compound biological activity. These results provide new candidate molecules for the development of treatments against Chagas disease.

Efficient identification of novel anti-glioma lead compounds by machine learning models.

Glioblastoma multiforme (GBM) is the most devastating and widespread primary central nervous system tumor. Pharmacological treatment of this malignance is limited by the selective permeability of the blood-brain barrier (BBB) and relies on a single drug, temozolomide (TMZ), thus making the discovery of new compounds challenging and urgent. Therefore, aiming to discover new anti-glioma drugs, we developed robust machine learning models for predicting anti-glioma activity and BBB penetration ability of new compounds. Using these models, we prioritized 41 compounds from our in-house library of compounds, for further in vitro testing against three glioma cell lines and astrocytes. Subsequently, the most potent and selective compounds were resynthesized and tested in vivo using an orthotopic glioma model. This approach revealed two lead candidates, 4m and 4n, which efficiently decreased malignant glioma development in mice, probably by inhibiting thioredoxin reductase activity, as shown by our enzymological assays. Moreover, these two compounds did not promote body weight reduction, death of animals, or altered hematological and toxicological markers, making then good candidates for lead optimization as anti-glioma drug candidates.

Dealing with frequent hitters in drug discovery: a multidisciplinary view on the issue of filtering compounds on biological screenings.

Introduction: The timely identification biologically active chemicals, in disease relevant screening assays, is a major endeavor in drug discovery. The existence of frequent hitters (FHs) in non-related assays poses a formidable challenge in terms of whether to consider these molecules as chemical gold or promiscuous non-selective reactive trash (also known as PAINS - pan assay interference compounds).Areas covered: In this review, the authors bring together expertize in synthetic chemistry, cheminformatics and biochemistry, three key areas for dealing with FHs. They discuss synthetic methods facilitating preparation of chemically diverse molecular libraries, while favoring activity in the biological space. They also survey and discuss recent computational advances in the prediction of PAINS from chemical structures. Finally, they review experimental approaches for the validation of the biological activity of screening hits and discuss alternatives for exploiting promiscuity and chemical reactivity.Expert opinion: It's essential to develop more efficient computational methods to reliably recognize PAINS in distinct molecular environments. Accordingly, advances in synthetic chemistry hold the promise to provide a better quality of chemical matter for drug discovery. Medicinal chemists should be more open to screening for hits showing biologically complex mechanisms of action rather than discarding molecules that may prove valuable as innovative disease treatments.

Discovery of new Schistosoma mansoni aspartyl protease inhibitors by structure-based virtual screening

BACKGROUND Schistosomiasis is a neglected tropical disease caused by trematodes of the genus Schistosoma, with a limited treatment, mainly based on the use of praziquantel (PZQ). Currently, several aspartic proteases genes have already been identified within the genome of Schistosoma species. At least one enzyme encoded from this gene family (SmAP), named SmCD1, has been validated for the development of schistosomicidal drugs, since it has a key role in haemoglobin digestion by worms. OBJECTIVE In this work, we integrated a structure-based virtual screening campaign, enzymatic assays and adult worms ex vivo experiments aiming to discover the first classes of SmCD1 inhibitors. METHODS Initially, the 3D-structures of SmCD1, SmCD2 and SmCD3 were generated using homology modelling approach. Using these models, we prioritised 50 compounds from 20,000 compounds from ChemBridge database for further testing in adult worm aqueous extract (AWAE) and recombinant SmCD1 using enzymatic assays. FINDINGS Seven compounds were confirmed as hits and among them, two compounds representing new chemical scaffolds, named 5 and 19, had IC50 values against SmCD1 close to 100 μM while presenting binding efficiency indexes comparable to or even higher than pepstatin, a classical tight-binding peptide inhibitor of aspartyl proteases. Upon activity comparison against mammalian enzymes, compound 50 was selective and the most potent against the AWAE aspartic protease activity (IC50 = 77.7 μM). Combination of computational and experimental results indicate that compound 50 is a selective inhibitor of SmCD2. Compounds 5, 19 and 50 tested at low concentrations (10 uM) were neither cytotoxic against WSS-1 cells (48 h) nor could kill adult worms ex-vivo, although compounds 5 and 50 presented a slight decrease on female worms motility on late incubations times (48 or 72 h). MAIN CONCLUSION Overall, the inhibitors identified in this work represent promising hits for further hit-to-lead optimisation.

Conservation analysis and decomposition of residue correlation networks in the phospholipase A2 superfamily (PLA2s): Insights into the structure-function relationships of snake venom toxins.

Phospholipases A2 (PLA2s) comprise a superfamily of glycerophospholipids hydrolyzing enzymes present in many organisms in nature, whose catalytic activity was majorly unveiled by analysis of snake venoms. The latter have pharmaceutical and biotechnological interests and can be divided into different functional sub-classes. Our goal was to identify important residues and their relation to the functional and class-specific characteristics in the PLA2s family with special emphasis on snake venom PLA2s (svPLA2s). We identified such residues by conservation analysis and decomposition of residue coevolution networks (DRCN), annotated the results based on the available literature on PLA2s, structural analysis and molecular dynamics simulations, and related the results to the phylogenetic distribution of these proteins. A filtered alignment of PLA2s revealed 14 highly conserved positions and 3 sets of coevolved residues, which were annotated according to their structural or functional role. These residues are mostly involved in ligand binding and catalysis, calcium-binding, the formation of disulfide bridges and a hydrophobic cluster close to the binding site. An independent validation of the inference of structure-function relationships from our co-evolution analysis on the svPLA2s family was obtained by the analysis of the pattern of selection acting on the Viperidae and Elapidae lineages. Additionally, a molecular dynamics simulation on the Lys49 PLA2 from Agkistrodon contortrix laticinctus was carried out to further investigate the correlation of the Lys49-Glu69 pair. Our results suggest this configuration can result in a novel conformation where the binding cavity collapses due to the approximation of two loops caused by a strong salt bridge between Glu69 and Arg34. Finally, phylogenetic analysis indicated a correlation between the presence of residues in the coevolved sets found in this analysis and the clade localization. The results provide a guide for important positions in the family of PLA2s, and potential new objects of investigation.