The Brazilian compound library (BraCoLi) database: a repository of chemical and biological information for drug design

A critical assessment of bioactive compounds databases

Compound databases (DBs) are essential tools for drug discovery. The number of DBs in public domain is increasing, so it is important to analyze these DBs. In this article, the main characteristics of 64 DBs will be presented. The methodological strategy used was a literature search. To analyze the characteristics obtained in the review, the DBs were categorized into two subsections: Open Access and Commercial DBs. Open access includes generalist DBs (containing compounds of diverse origins), DBs with specific applicability, DBs exclusive to natural products and those containing compounds with specific pharmacological action. The literature review showed that there are challenges to making these repositories available, such as standardizing information curation practices and funding to maintain and sustain them.

Machine Learning-Based Virtual Screening of Antibacterial Agents against Methicillin-Susceptible and Resistant Staphylococcus aureus

The application of computer-aided drug discovery (CADD) approaches has enabled the discovery of new antimicrobial therapeutic agents in the past. The high prevalence of methicillin-resistantStaphylococcus aureus(MRSA) strains promoted this pathogen to a high-priority pathogen for drug development. In this sense, modern CADD techniques can be valuable tools for the search for new antimicrobial agents. We employed a combination of a series of machine learning (ML) techniques to select and evaluate potential compounds with antibacterial activity against methicillin-susceptible S. aureus (MSSA) and MRSA strains. In the present study, we describe the antibacterial activity of six compounds against MSSA and MRSA reference (American Type Culture Collection (ATCC)) strains as well as two clinical strains of MRSA. These compounds showed minimal inhibitory concentrations (MIC) in the range from 12.5 to 200 μM against the different bacterial strains evaluated. Our results constitute relevant proven ML-workflow models to distinctively screen for novel MRSA antibiotics.

In silico evaluation of pharmacokinetics properties of withanolides and simulation of their biological activities against Alzheimer's disease

The withanolides are naturally occurring steroidal lactones found mainly in plants of the Solanaceae family. The subtribe Withaninae includes species like Withania sominifera, which are a source of many bioactive withanolides. In this work, we selected and evaluate the ADMET-related properties of 91 withanolides found in species of the subtribe Withaninae computationally, to predict the relationship between their structures and their pharmacokinetic profiles. We also evaluated the interaction of these withanolides with known targets of Alzheimer's disease (AD) through molecular docking and molecular dynamics. Withanolides presented favorable pharmacokinetic properties, like high gastrointestinal absorption, lipophilicity (logP ≤ 5), good distribution and excretion parameters, and a favorable toxicity profile. The specie Withania aristata stood out as an interesting source of the promising withanolides classified as 5-ene with 16-ene or 17-ene. These withanolides presented a favourable pharmacokinetic profile and were also highlighted as the best candidates for inhibition of AD-related targets. Our results also suggest that withanolides are likely to act as cholinesterase inhibitors by interacting with the catalytic pocket in an energy favorable and stable way.Communicated by Ramaswamy H. Sarma.

Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach

Around three billion people are at risk of infection by the dengue virus (DENV) and potentially other flaviviruses. Worldwide outbreaks of DENV, Zika virus (ZIKV), and yellow fever virus (YFV), the lack of antiviral drugs, and limitations on vaccine usage emphasize the need for novel antiviral research. Here, we propose a consensus virtual screening approach to discover potential protease inhibitors (NS3pro) against different flavivirus. We employed an in silico combination of a hologram quantitative structure-activity relationship (HQSAR) model and molecular docking on characterized binding sites followed by molecular dynamics (MD) simulations, which filtered a data set of 7.6 million compounds to 2,775 hits. Lastly, docking and MD simulations selected six final potential NS3pro inhibitors with stable interactions along the simulations. Five compounds had their antiviral activity confirmed against ZIKV, YFV, DENV-2, and DENV-3 (ranging from 4.21 ± 0.14 to 37.51 ± 0.8 μM), displaying aggregator characteristics for enzymatic inhibition against ZIKV NS3pro (ranging from 28 ± 7 to 70 ± 7 μM). Taken together, the compounds identified in this approach may contribute to the design of promising candidates to treat different flavivirus infections.

Structure-based discovery of thiosemicarbazones as SARS-CoV-2 main protease inhibitors

Aim: Discovery of novel SARS-CoV-2 main protease (Mpro) inhibitors using a structure-based drug discovery strategy. Materials & methods: Virtual screening employing covalent and noncovalent docking was performed to discover Mpro inhibitors, which were subsequently evaluated in biochemical and cellular assays. Results: 91 virtual hits were selected for biochemical assays, and four were confirmed as reversible inhibitors of SARS CoV-2 Mpro with IC50 values of 0.4-3 μM. They were also shown to inhibit SARS-CoV-1 Mpro and human cathepsin L. Molecular dynamics simulations indicated the stability of the Mpro inhibitor complexes and the interaction of ligands at the subsites. Conclusion: This approach led to the discovery of novel thiosemicarbazones as potent SARS-CoV-2 Mpro inhibitors.

Screening the Pathogen Box to Discover and Characterize New Cruzain and TbrCatL Inhibitors

Chagas disease and Human African Trypanosomiasis, caused by Trypanosoma cruzi and T. brucei, respectively, pose relevant health challenges throughout the world, placing 65 to 70 million people at risk each. Given the limited efficacy and severe side effects associated with current chemotherapy, new drugs are urgently needed for both diseases. Here, we report the screening of the Pathogen Box collection against cruzain and TbrCatL, validated targets for Chagas disease and Human African Trypanosomiasis, respectively. Enzymatic assays were applied to screen 400 compounds, validate hits, determine IC₅₀ values and, when possible, mechanisms of inhibition. In this case, 12 initial hits were obtained and ten were prioritized for follow-up. IC₅₀ values were obtained for six of them (hit rate = 1.5%) and ranged from 0.46 ± 0.03 to 27 ± 3 µM. MMV687246 was found to be a mixed inhibitor of cruzain (K_i = 57 ± 6 µM) while MMV688179 was found to be a competitive inhibitor of cruzain with a nanomolar potency (K_i = 165 ± 63 nM). A putative binding mode for MMV688179 was obtained by docking. The six hits discovered against cruzain and TbrCatL are of great interest for further optimization by the medicinal chemistry community.