The nature of ligand efficiency

Synthesis and biological evaluation of orally active anti-Trypanosoma agents

In previous studies, we developed anti-trypanosome tubulin inhibitors with promising in vitro selectivity and activity against Human African Trypanosomiasis (HAT). However, for such agents, oral activity is crucial. This study focused on further optimizing these compounds to enhance their ligand efficiency, aiming to reduce bulkiness and hydrophobicity, which should improve solubility and, consequently, oral bioavailability. Using Trypanosoma brucei brucei cells as the parasite model and human normal kidney cells and mouse macrophage cells as the host model, we evaluated 30 new analogs synthesized through combinatorial chemistry. These analogs have fewer aromatic moieties and lower molecular weights than their predecessors. Several new analogs demonstrated IC50s in the low micromolar range, effectively inhibiting trypanosome cell growth without harming mammalian cells at the same concentration. We conducted a detailed structure-activity relationship (SAR) analysis and a docking study to assess the compounds' binding affinity to trypanosome tubulin homolog. The results revealed a correlation between binding energy and anti-Trypanosoma activity. Importantly, compound 7 displayed significant oral activity, effectively inhibiting trypanosome cell proliferation in mice.

Synthesis, In Silico Study, and In Vitro Antifungal Activity of New 5-(1,3-Diphenyl-1H-Pyrazol-4-yl)-4-Tosyl-4,5-Dihydrooxazoles

The increase in multi-drug resistant Candida strains has caused a sharp rise in life-threatening fungal infections in immunosuppressed patients, including those with SARS-CoV-2. Novel antifungal drugs are needed to combat multi-drug-resistant yeasts. This study aimed to synthesize a new series of 2-oxazolines and evaluate the ligands in vitro for the inhibition of six Candida species and in silico for affinity to the CYP51 enzymes (obtained with molecular modeling and protein homology) of the same species. The 5-(1,3-diphenyl-1H-pyrazol-4-yl)-4-tosyl-4,5-dihydrooxazoles 6a-j were synthesized using the Van Leusen reaction between 1,3-diphenyl-4-formylpyrazoles 4a-j and TosMIC 5 in the presence of K2CO3 or KOH without heating, resulting in short reaction times, high compound purity, and high yields. The docking studies revealed good affinity for the active site of the CYP51 enzymes of the Candida species in the following order: 6a-j > 4a-j > fluconazole (the reference drug). The in vitro testing of the compounds against the Candida species showed lower MIC values for 6a-j than 4a-j, and for 4a-j than fluconazole, thus correlating well with the in silico findings. According to growth rescue assays, 6a-j and 4a-j (like fluconazole) inhibit ergosterol synthesis. The in silico toxicity assessment evidenced the safety of compounds 6a-j, which merit further research as possible antifungal drugs.

PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs

Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/.

Plant exosome-like nanovesicles derived from sesame leaves as carriers for luteolin delivery: Molecular docking, stability and bioactivity

The growing recognition of luteolin (Lu) as a vital functional component is attributed to its notable bioactive properties. However, the effective use of Lu is hindered by its inherent limitations related to water solubility, stability, and bioavailability. Here, we aim to develop sesame leaves-derived exosome-like nanovesicles (Exo) for Lu delivery (Exo@Lu) as vehicles. The encapsulation mechanism, solubility, stability, and bioactivity of Exo@Lu were thoroughly evaluated. Exo enriched abundant lipids, proteins, and phenolic compounds with an encapsulation efficiency of ∼ 91.9 % and a loading capacity of ∼ 20.5 % for Lu. The primary binding forces responsible for the encapsulation were hydrogen bonds and van der Waals forces. After encapsulation, the water solubility and stability of Lu were significantly improved under various conditions, including thermal, light, storage, ionic strength, and pH. Exo@Lu maintained structural integrity during simulated digestion, enhancing bioaccessibility and efficacy in mitigating oxidative stress and inflammatory response compared to Exo and free Lu.

In silico toxicity and immunological interactions of components of calcium silicate-based and epoxy resin-based endodontic sealers

OBJECTIVES

The present study aimed to determine in silico toxicity predictions of test compounds from hydraulic calcium silicate-based sealers (HCSBS) and AH Plus and computationally simulate the interaction between these substances and mediators of periapical inflammation via molecular docking.

MATERIALS AND METHODS

All chemical information of the test compounds was obtained from the PubChem site. Predictions for bioavailability and toxicity analyses were determined by the Molinspiration Cheminformatics, pkCSM, ProTox-II and OSIRIS Property Explorer platforms. Molecular docking was performed using the Autodock4 AMDock v.1.5.2 program to analyse interactions between proteins (IL-1β, IL-6, IL-8, IL-10 and TNF-α) and ligands (calcium silicate hydrate, zirconium oxide, bisphenol-A epoxy resin, dibenzylamine, iron oxide and calcium tungstate) to establish the affinity and bonding mode between systems.

RESULTS

Bisphenol-A epoxy resin had the lowest maximum dose tolerated in humans and was the test compound with the largest number of toxicological properties (hepatotoxicity, carcinogenicity and irritant). All systems had favourable molecular docking. However, the ligands bisphenol-A epoxy resin and dibenzylamine had the greatest affinity with the cytokines tested.

CONCLUSION

In silico predictions and molecular docking pointed the higher toxicity and greater interaction with mediators of periapical inflammation of the main test compounds from AH Plus compared to those from HCSBS.

CLINICAL RELEVANCE

This is the first in silico study involving endodontic materials and may serve as the basis for further research that can generate more data, producing knowledge on the interference of each chemical compound in the composition of different root canal sealers.

A miniaturized mode-of-action profiling platform enables high throughput characterization of the molecular and cellular dynamics of EZH2 inhibition

The market approval of Tazemetostat (TAZVERIK) for the treatment of follicular lymphoma and epithelioid sarcoma has established "enhancer of zeste homolog 2" (EZH2) as therapeutic target in oncology. Despite their structural similarities and common mode of inhibition, Tazemetostat and other EZH2 inhibitors display differentiated pharmacological profiles based on their target residence time. Here we established high throughput screening methods based on time-resolved fluorescence energy transfer, scintillation proximity and high content analysis microscopy to quantify the biochemical and cellular binding of a chemically diverse collection of EZH2 inhibitors. These assays allowed to further characterize the interplay between EZH2 allosteric modulation by methylated histone tails (H3K27me3) and inhibitor binding, and to evaluate the impact of EZH2's clinically relevant mutant Y641N on drug target residence times. While all compounds in this study exhibited slower off-rates, those with clinical candidate status display significantly slower target residence times in wild type EZH2 and disease-related mutants. These inhibitors interact in a more entropy-driven fashion and show the most persistent effects in cellular washout and antiproliferative efficacy experiments. Our work provides mechanistic insights for the largest cohort of EZH2 inhibitors reported to date, demonstrating that-among several other binding parameters-target residence time is the best predictor of cellular efficacy.

Discovery of pyrazolo[3,4-d]pyrimidines as novel mitogen-activated protein kinase kinase 3 (MKK3) inhibitors

The dual-specificity protein kinase MKK3 has been implicated in tumor cell proliferation and survival, yet its precise role in cancer remains inconclusive. A critical step in elucidating the kinase's involvement in disease biology is the identification of potent, cell-permeable kinase inhibitors. Presently, MKK3 lacks a dedicated tool compound for these purposes, along with validated methods for the facile screening, identification, and optimization of inhibitors. In this study, we have developed a TR-FRET-based enzymatic assay for the detection of MKK3 activity in vitro and a BRET-based assay to assess ligand binding to this enzyme within intact human cells. These assays were instrumental in identifying hit compounds against MKK3 that share a common chemical scaffold, sourced from a library of bioactive kinase inhibitors. Initial hits were subsequently expanded through the synthesis of novel analogs. The resulting structure-activity relationship (SAR) was rationalized using molecular dynamics simulations against a homology model of MKK3. We expect our findings to expedite the development of novel, potent, selective, and bioactive inhibitors, thus facilitating investigations into MKK3's role in various cancers.

Geometric Deep Learning for Structure-Based Ligand Design

A pervasive challenge in drug design is determining how to expand a ligand-a small molecule that binds to a target biomolecule-in order to improve various properties of the ligand. Adding single chemical groups, known as fragments, is important for lead optimization tasks, and adding multiple fragments is critical for fragment-based drug design. We have developed a comprehensive framework that uses machine learning and three-dimensional protein-ligand structures to address this challenge. Our method, FRAME, iteratively determines where on a ligand to add fragments, selects fragments to add, and predicts the geometry of the added fragments. On a comprehensive benchmark, FRAME consistently improves predicted affinity and selectivity relative to the initial ligand, while generating molecules with more drug-like chemical properties than docking-based methods currently in widespread use. FRAME learns to accurately describe molecular interactions despite being given no prior information on such interactions. The resulting framework for quality molecular hypothesis generation can be easily incorporated into the workflows of medicinal chemists for diverse tasks, including lead optimization, fragment-based drug discovery, and de novo drug design.

The anticancer potential of chemical constituents of Moringa oleifera targeting CDK-2 inhibition in estrogen receptor positive breast cancer using in-silico and in vitro approches

Most of the breast cancers are estrogen receptor-positive recurring with a steady rate of up to 20 years dysregulating the normal cell cycle. Dinaciclib is still in clinical trials and considered as a research drug against such cancers targeting CDK2.The major goal of this study was to identify the potential inhibitors of CDK-2 present in Moringa oleifera for treating hormonal receptor positive breast cancers. For this purpose, in silico techniques; molecular docking, MM-GBSA and molecular dynamics simulations were employed to screen Moringa oleifera compounds and their anticancer potential was determined against CDK-2 protein targets. Among 36 compounds of Moringa oleifera reported in literature, chlorogenic acid (1), quercetin (2), ellagic acid (3), niazirin (4), and kaempferol (5) showed good affinity with the target. The interaction of the compounds was visualized using PYMOL software. The profiles of absorption, distribution, metabolism, excretion (ADME) and toxicity were determined using SWISS and ProTox II webservers. The MTT assay was performed in-vitro using MCF-7 cancer cell lines to validate the anticancer potential of Moringa oleifera leaf extract.MTT assay results revealed no significant change in proliferation of Mcf-7 cells following 24 h treatment with fraction A (petroleum ether). However, significant antiproliferative effect was observed at 200 µg/mL dose of fraction B (ethyl acetate) and cell viability was reduced to 40%.In conclusion, the data suggested that all the compounds with highest negative docking score than the reference could be the potential candidates for cyclin dependent kinase-2 (CDK-2) inhibition while ellagic acid, chlorogenic acid and quercetin being the most stable and potent inhibitors to treat estrogen receptor positive breast cancer targeting CDK-2. Moreover, the data suggested that further investigation is required to determine the optimum dose for significant antiproliferative effects using in-vivo models to validate our findings of in-silico analysis.

Towards holistic Compound Quality Scores: Extending ligand efficiency indices with compound pharmacokinetic characteristics

The suitability of small molecules as oral drugs is often assessed by simple physicochemical rules, the application of ligand efficiency scores or by composite scores based on physicochemical compound properties. These rules and scores are empirical and typically lack mechanistic background, such as information on pharmacokinetics (PK). We introduce new types of Compound Quality Scores (CQS, specifically called dose scores and cmax scores), which explicitly include predicted or, when available, experimental PK parameters and combine these with on-target potency. These CQS scores are surrogates for an estimated dose and corresponding cmax and allow prioritizing of compounds within test cascades as well as before synthesis. We demonstrate the complementarity and, in most cases, superior performance relative to existing efficiency metrics by project examples.

Combining docking, molecular dynamics simulations, AD-MET pharmacokinetics properties, and MMGBSA calculations to create specialized protocols for running effective virtual screening campaigns on the autoimmune disorder and SARS-CoV-2 main protease

The development of novel medicines to treat autoimmune diseases and SARS-CoV-2 main protease (Mpro), a virus that can cause both acute and chronic illnesses, is an ongoing necessity for the global community. The primary objective of this research is to use CoMFA methods to evaluate the quantitative structure-activity relationship (QSAR) of a select group of chemicals concerning autoimmune illnesses. By performing a molecular docking analysis, we may verify previously observed tendencies and gain insight into how receptors and ligands interact. The results of the 3D QSAR models are quite satisfactory and give significant statistical results: Q_loo∧2 = 0.5548, Q_lto∧2 = 0.5278, R∧2 = 0.9990, F-test = 3,101.141, SDEC = 0.017 for the CoMFA FFDSEL, and Q_loo∧2 = 0.7033, Q_lto∧2 = 0.6827, Q_lmo∧2 = 0.6305, R∧2 = 0.9984, F-test = 1994.0374, SDEC = 0.0216 for CoMFA UVEPLS. The success of these two models in exceeding the external validation criteria used and adhering to the Tropsha and Glorbaikh criteria's upper and lower bounds can be noted. We report the docking simulation of the compounds as an inhibitor of the SARS-CoV-2 Mpro and an autoimmune disorder in this context. For a few chosen autoimmune disorder receptors (protein tyrosine phosphatase, nonreceptor type 22 (lymphoid) isoform 1 (PTPN22), type 1 diabetes, rheumatoid arthritis, and SARS-CoV-2 Mpro, the optimal binding characteristics of the compounds were described. According to their potential for effectiveness, the studied compounds were ranked, and those that demonstrated higher molecular docking scores than the reference drugs were suggested as potential new drug candidates for the treatment of autoimmune disease and SARS-CoV-2 Mpro. Additionally, the results of analyses of drug similarity, ADME (Absorption, Distribution, Metabolism, and Excretion), and toxicity were used to screen the best-docked compounds in which compound 4 scaled through. Finally, molecular dynamics (MD) simulation was used to verify compound 4's stability in the complex with the chosen autoimmune diseases and SARS-CoV-2 Mpro protein. This compound showed a steady trajectory and molecular characteristics with a predictable pattern of interactions. These findings suggest that compound 4 may hold potential as a therapy for autoimmune diseases and SARS-CoV-2 Mpro.

2-Alkyl-Substituted-4-Amino-Thieno[2,3-d]Pyrimidines: Anti-Proliferative Properties to In Vitro Breast Cancer Models

Thienopyrimidines are structural analogs of quinazolines, and the creation of new 2-alkyl derivatives of ethyl 4-aminothienopyrimidine-6-carboxylates for the study of their anti-proliferative properties is of great pharmacological interest. Some 2-alkyl-4-amino-thieno[2,3-d]pyrimidines 2-5 were synthesized, and their cyto- and phototoxicity against BALB 3T3 cells were established by an in vitro 3T3 NRU test. The obtained results indicate that the tested compounds are not cytotoxic or phototoxic, and that they are appropriate to be studied for their anti-proliferative and anti-tumor properties. The anti-proliferative potential of the compounds was investigated on MCF-7 and MDA-MB-231 cancer cells, as well as a MCF-10A cell line (normal human mammary epithelial cells). The most toxic to MCF-7 was thienopyrimidine 3 with IC50 13.42 μg/mL (IC50 0.045 μM), followed by compound 4 (IC50 28.89 μg/mL or IC50 0.11 μM). The thienopyrimidine 4 revealed higher selectivity to MCF-7 and lower activity (IC50 367 μg/mL i.e., 1.4 μM) than compound 3 with MCF-10A cells. With respect to MDA-MB-231 cells, ester 2 manifested the highest effect with IC50 52.56 μg/mL (IC50 0.16 μM), and 2-ethyl derivative 4 revealed IC50 62.86 μg/mL (IC50 0.24 μM). It was estimated that the effect of the substances on the cell cycle progression was due to cell cycle arrest in the G2 stage for MDA-MB-231, while arrest in G1 was detected for the estrogen (ER)-positive MCF-7 cell line. The tested compound's effects on the change of the zeta potential in the tumorigenic cells utilized in this study were determined. The calculation which we performed of the physicochemical properties and pharmacokinetic parameters influencing the biological activity suggested high intestinal absorption, as well as drug-likeness.

Computational Fragment-Based Design of Phytochemical Derivatives as EGFR Inhibitors

Epidermal growth factor receptor (EGFR) is a potential target with disease modifying benefits against Alzheimer's disease (AD). Repurposing of FDA approved drugs against EGFR have shown beneficial effect against AD but are confined to quinazoline, quinoline and aminopyrimidines. Futuristically, the possibility of acquiring drug resistance mutation as seen in the case of cancer could also hamper AD treatment. To identify novel chemical scaffolds, we rooted on phytochemicals identified from plants such as Acorus calamus, Bacopa monnieri, Convolvulus pluricaulis, Tinospora cordifloia, and Withania somnifera that have well-established records in the treatment of brain disorders. The rationale was to mimic the biosynthetic metabolite extension process observed in the plants for synthesizing new phytochemical derivates. Thus, novel compounds were designed computationally by fragment-based method followed by extensive in silico analysis to pick potential phytochemical derivates. PCD1, 8 and 10 were predicted to have better blood brain barrier permeability. ADMET and SoM analysis suggested that these PCDs exhibited druglike properties. Further simulation studies showed that PCD1 and PCD8 stably interact with EGFR and have the potential to be used even in cases of drug-resistance mutations. With further experimental evidence, these PCDs could be leveraged as potential inhibitors of EGFR.

Preferred microenvironments of halogen bonds and hydrogen bonds revealed using statistics and QM/MM calculation studies

Hydrogen bonds (HBs) and halogen bonds (XBs) are two essential non-covalent interactions for molecular recognition and drug design. As proteins are heterogeneous in structure, the microenvironments of protein structures should have effects on the formation of HBs and XBs with ligands. However, there are no systematic studies reported on this effect to date. For quantitatively describing protein microenvironments, we defined the local hydrophobicities (LHs) and local dielectric constants (LDCs) in this study. With the defined parameters, we conducted an elaborate database survey on the basis of 22 011 ligand-protein structures to explore the microenvironmental preference of HBs (91 966 in total) and XBs (1436 in total). The statistics show that XBs prefer hydrophobic microenvironments compared to HBs. The polar residues like ASP are more likely to form HBs with ligands, while nonpolar residues such as PHE and MET prefer XBs. Both the LHs and LDCs (10.69 ± 4.36 for HBs; 8.86 ± 4.00 for XBs) demonstrate that XBs are prone to hydrophobic microenvironments compared with HBs with significant differences (p < 0.001), indicating that evaluating their strengths in the corresponding environments should be necessary. Quantum Mechanics-Molecular Mechanics (QM/MM) calculations reveal that in comparison with vacuum environments, the interaction energies of HBs and XBs are decreased to varying degrees given different microenvironments. In addition, the strengths of HBs are impaired more than those of XBs when the local dielectric constant's difference between the XB microenvironments and the HB microenvironments is large.

Threat of respiratory syncytial virus infection knocking the door: a proposed potential drug candidate through molecular dynamics simulations, a future alternative

The discovery of antiviral approaches to prevent or cure respiratory syncytial virus (RSV) infections is critical, particularly because RSV is one of the most common causes of infant respiratory problems. There is currently no approved vaccination available to treat RSV infections. FDA has approved the drug ribavirin, but it is not sufficient to treat RSV. This work aimed to find and study in silico anti-RSV drugs that target matrix protein and nucleoprotein. In this study, we have identified five drug candidates that had better binding energies than ribavirin. Garenoxacin appeared as top lead compounds between them. AutoDock Vina was used to execute molecular docking of a library of chosen chemicals. The high-score compound was then confirmed using the Maestro 12.3 module's molecular dynamics simulation and the binding energies derived using Prime/Molecular Mechanics Generalized Born Surface Area (Prime/MM-GBSA). Comparative molecular dynamics simulations revealed that garenoxacin has better stability and high residue contacts with high binding affinity than ribavirin. This study showed garenoxacin could prevent RSV infection better than ribavirin. In pursuing a more effective RSV control drug, additional research into these chemicals in vitro and in vivo is essential.

A Distributional Model of Bound Ligand Conformational Strain: From Small Molecules up to Large Peptidic Macrocycles

The internal conformational strain incurred by ligands upon binding a target site has a critical impact on binding affinity, and expectations about the magnitude of ligand strain guide conformational search protocols. Estimates for bound ligand strain begin with modeled ligand atomic coordinates from X-ray co-crystal structures. By deriving low-energy conformational ensembles to fit X-ray diffraction data, calculated strain energies are substantially reduced compared with prior approaches. We show that the distribution of expected global strain energy values is dependent on molecular size in a superlinear manner. The distribution of strain energy follows a rectified normal distribution whose mean and variance are related to conformational complexity. The modeled strain distribution closely matches calculated strain values from experimental data comprising over 3000 protein-ligand complexes. The distributional model has direct implications for conformational search protocols as well as for directions in molecular design.

The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy

The modern development of computer technology and different in silico methods have had an increasing impact on the discovery and development of new drugs. Different molecular docking techniques most widely used in silico methods in drug discovery. Currently, the time and financial costs for the initial hit identification can be significantly reduced due to the ability to perform high-throughput virtual screening of large compound libraries in a short time. However, the selection of potential hit compounds still remains more of a random process, because there is still no consensus on what the binding energy and ligand efficiency (LE) of a potentially active compound should be. In the best cases, only 20-30% of compounds identified by molecular docking are active in biological tests. In this work, we evaluated the impact of the docking software used as well as the type of the target protein on the molecular docking results and their accuracy using an example of the three most popular programs and five target proteins related to neurodegenerative diseases. In addition, we attempted to determine the "reliable range" of the binding energy and LE that would allow selecting compounds with biological activity in the desired concentration range.

Combination of Docking-Based and Pharmacophore-Based Virtual Screening Identifies Novel Agonists That Target the Urotensin Receptor

The urotensin receptor (UT receptor), a G-protein-coupled receptor mediating urotensin-II and urotensin-II-related peptide signaling in the urotensinergic system, has multiple pharmacological activities. However, there is no drug targeting the UT receptor currently in clinical use, and the discovery of new leads is still important. The complete crystal structure of the UT receptor has not yet been resolved and a screening strategy combining multiple methods can improve the accuracy and efficiency of drug screening. This study aimed to identify novel UT receptor agonists using a combination of docking-based, pharmacophore-based, and cell-based drug screening. First, the three-dimensional structures of the UT receptor were constructed through single-template, multi-template homologous modeling and threading strategies. After structure evaluation and ligand enrichment analysis, a model from the threading modeling was selected for docking-based virtual screening based on stepwise filtering, and 1368 positive compounds were obtained from our compound library. Second, the pharmacophore models were constructed using known ligands targeting the UT receptor for pharmacophore-based virtual screening. A model was selected after model validation, and 300 positive compounds were retrieved. Then, after intersecting the results of two different virtual screening methods with 570 compound entities from our primary screening, 14 compounds were obtained. Finally, three hits were obtained after in vitro confirmation. Furthermore, preliminary evaluation of the hits showed that they influenced glucose consumption. In summary, by integrating docking-based, pharmacophore-based, and in vitro drug screening, three new agonists targeting the UT receptor were identified which may serve as promising therapeutic agents for urotensinergic system disorders.

Natural Compounds as Non-Nucleoside Inhibitors of Zika Virus Polymerase through Integration of In Silico and In Vitro Approaches

Although the past epidemic of Zika virus (ZIKV) resulted in severe neurological consequences for infected infants and adults, there are still no approved drugs to treat ZIKV infection. In this study, we applied computational approaches to screen an in-house database of 77 natural and semi-synthetic compounds against ZIKV NS5 RNA-dependent RNA-polymerase (NS5 RdRp), an essential protein for viral RNA elongation during the replication process. For this purpose, we integrated computational approaches such as binding-site conservation, chemical space analysis and molecular docking. As a result, we prioritized nine virtual hits for experimental evaluation. Enzymatic assays confirmed that pedalitin and quercetin inhibited ZIKV NS5 RdRp with IC₅₀ values of 4.1 and 0.5 µM, respectively. Moreover, pedalitin also displayed antiviral activity on ZIKV infection with an EC₅₀ of 19.28 µM cell-based assays, with low toxicity in Vero cells (CC₅₀ = 83.66 µM) and selectivity index of 4.34. These results demonstrate the potential of the natural compounds pedalitin and quercetin as candidates for structural optimization studies towards the discovery of new anti-ZIKV drug candidates.

In Combo Studies for the Optimization of 5-Aminoanthranilic Acid Derivatives as Potential Multitarget Drugs for the Management of Metabolic Syndrome

Metabolic syndrome is a set of risk factors that consist of abdominal obesity, arterial hypertension, alterations in the lipid profile, and hyperglycemia. The current therapeutic strategy includes polypharmacy, using three or more drugs to control each syndrome component. However, this approach has drawbacks that could lead to therapeutic failure. Multitarget drugs are molecules with the ability to act on different targets simultaneously and are an attractive alternative for treating complex diseases such as metabolic syndrome. Previously, we identified a triamide derivative of 5-aminoanthranilic acid that exhibited hypoglycemic, hypolipemic, and antihypertensive activities simultaneously. In the present study, we report the synthesis and in combo evaluation of new derivatives of anthranilic acid, intending to identify the primary structural factors that improve the activity over metabolic syndrome-related parameters. We found that substitution on position 5, incorporation of 3,4-dimethoxyphenyl substituents, and having a free carboxylic acid group lead to the in vitro inhibition of HMG-CoA reductase, and simultaneously the diminution of the serum levels of glucose, triglycerides, and cholesterol in a diet-induced in vivo model.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying “magic bullets” amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand–target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural–energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

Identification of Potential Insect Growth Inhibitor against Aedes aegypti: A Bioinformatics Approach

Aedes aegypti is the main vector that transmits viral diseases such as dengue, hemorrhagic dengue, urban yellow fever, zika, and chikungunya. Worldwide, many cases of dengue have been reported in recent years, showing significant growth. The best way to manage diseases transmitted by Aedes aegypti is to control the vector with insecticides, which have already been shown to be toxic to humans; moreover, insects have developed resistance. Thus, the development of new insecticides is considered an emergency. One way to achieve this goal is to apply computational methods based on ligands and target information. In this study, sixteen compounds with acceptable insecticidal activities, with 100% larvicidal activity at low concentrations (2.0 to 0.001 mg·L−1), were selected from the literature. These compounds were used to build up and validate pharmacophore models. Pharmacophore model 6 (AUC = 0.78; BEDROC = 0.6) was used to filter 4793 compounds from the subset of lead-like compounds from the ZINC database; 4142 compounds (dG < 0 kcal/mol) were then aligned to the active site of the juvenile hormone receptor Aedes aegypti (PDB: 5V13), 2240 compounds (LE < −0.40 kcal/mol) were prioritized for molecular docking from the construction of a chitin deacetylase model of Aedes aegypti by the homology modeling of the Bombyx mori species (PDB: 5ZNT), which aligned 1959 compounds (dG < 0 kcal/mol), and 20 compounds (LE < −0.4 kcal/mol) were predicted for pharmacokinetic and toxicological prediction in silico (Preadmet, SwissADMET, and eMolTox programs). Finally, the theoretical routes of compounds M01, M02, M03, M04, and M05 were proposed. Compounds M01−M05 were selected, showing significant differences in pharmacokinetic and toxicological parameters in relation to positive controls and interaction with catalytic residues among key protein sites reported in the literature. For this reason, the molecules investigated here are dual inhibitors of the enzymes chitin synthase and juvenile hormonal protein from insects and humans, characterizing them as potential insecticides against the Aedes aegypti mosquito.

Design, Cytotoxicity and Antiproliferative Activity of 4-Amino-5-methyl-thieno[2,3-d]pyrimidine-6-carboxylates against MFC-7 and MDA-MB-231 Breast Cancer Cell Lines

Novel 4-amino-thieno[2,3-d]pyrimidine-6-carboxylates substituted at the second position were prepared by cyclocondensation of 2-amino-3-cyano-thiophene and aryl nitriles in an acidic medium. The design of the target compounds was based on structural optimization. The derivatives thus obtained were tested in vitro against human and mouse cell lines. The examination of the compound effects on BLAB 3T3 and MFC-10A cells showed that they are safe, making them suitable for subsequent experiments to establish their antitumor activity. The photoirritancy factor of the compounds was calculated. Using the MTT test, the antiproliferative activity to MCF-10A, MCF-7 and MDA-MB-231 cell lines was estimated. The best antiproliferative effect in respect to the MCF-7 cell line revealed compound 2 with IC₅₀ 4.3 ± 0.11 µg/mL (0.013 µM). The highest selective index with respect to MCF-7 cells was shown by compound 3 (SI = 19.3), and to MDA-MB-231 cells by compound 2 (SI = 3.7). Based on energy analysis, the most stable conformers were selected and optimized by means of density functional theory (DFT). Ligand efficiency, ligand lipophilicity efficiency and the physicochemical parameters of the target 4-amino-thienopyrimidines were determined. The data obtained indicated that the lead compound among the tested substances is compound 2.

Unique Diacidic Fragments Inhibit the OXA-48 Carbapenemase and Enhance the Killing of Escherichia coli Producing OXA-48

Despite the advances in β-lactamase inhibitor development, limited options exist for the class D carbapenemase known as OXA-48. OXA-48 is one of the most prevalent carbapenemases in carbapenem-resistant Enterobacteriaceae infections and is not susceptible to most available β-lactamase inhibitors. Here, we screened various low-molecular-weight compounds (fragments) against OXA-48 to identify functional scaffolds for inhibitor development. Several biphenyl-, naphthalene-, fluorene-, anthraquinone-, and azobenzene-based compounds were found to inhibit OXA-48 with low micromolar potency despite their small size. Co-crystal structures of OXA-48 with several of these compounds revealed key interactions with the carboxylate-binding pocket, Arg214, and various hydrophobic residues of β-lactamase that can be exploited in future inhibitor development. A number of the low-micromolar-potency inhibitors, across different scaffolds, synergize with ampicillin to kill Escherichia coli expressing OXA-48, albeit at high concentrations of the respective inhibitors. Additionally, several compounds demonstrated micromolar potency toward the OXA-24 and OXA-58 class D carbapenemases that are prevalent in Acinetobacter baumannii. This work provides foundational information on a variety of chemical scaffolds that can guide the design of effective OXA-48 inhibitors that maintain efficacy as well as potency toward other major class D carbapenemases.

Investigation of Thiocarbamates as Potential Inhibitors of the SARS-CoV-2 Mpro

In the present study we tested, using the microscale thermophoresis technique, a small library of thionocarbamates, thiolocarbamates, sulfide and disulfide as potential lead compounds for SARS-CoV-2 Mpro drug design. The successfully identified binder is a representative of the thionocarbamates group with a high potential for future modifications aiming for higher affinity and solubility. The experimental analysis was extended by computational studies that show insufficient accuracy of the simplest and widely applied approaches and underline the necessity of applying more advanced methods to properly evaluate the affinity of potential SARS-CoV-2 Mpro binders.

Hepatoprotective Effects of Sweet Cherry Extracts (cv. Saco)

Cancer is the second cause of death worldwide. Among cancers, hepatocellular carcinoma is one of the most prevalent. Evidence indicates that the daily consumption of fruits and vegetables can prevent the onset of various cancers due to the presence of bioactive compounds. Sweet cherries are known for their richness in phenolics, including anthocyanins, which are the major constituents, and presumably, the key contributors to their biological activity. Therefore, the present study aimed to evaluate the effects of three different cherry fractions on human hepatocellular carcinoma (HepG2) cells viability and effectiveness to improve the redox status of these cells under oxidative damage induced by nitric oxide radicals and hydrogen peroxide. Phenolic characterization of fractions was performed by Fourier transform infrared spectroscopy. The obtained results indicated that enriched phenolic fractions of sweet cherries (cv. Saco, can impair cell viability and suppress cells growth after 72 h of exposure, promoting necrosis at the highest tested concentrations (>50 µg/mL). Additionally, fractions also showed the capacity to protect these cells against oxidative injury by capturing radicals before they can attack cells’ membrane and by modulating reactive oxygen and nitrogen species generation, as demonstrated by bioinformatic tools.

Structure-based virtual screening and molecular dynamics simulation studies to discover new SARS-CoV-2 main protease inhibitors

Computational methods were used to filter two datasets (> 8,000 compounds) based on two criteria: higher binding affinity for M^PRO than cocrystallized inhibitor and binding interactions with M^PRO catalytic dyad (Cys145 and His41). After virtual screening involving ranking and reranking, eleven compounds were identified to satisfy these criteria and analysis of their structures revealed an unparallel common features among them which could be critical for their interactions with M^PRO. However, only the topmost scoring compound (AV-203: K_i = 0.31 µM) exhibited relatively stable binding interaction during the period of 50 ns MD simulation and thus is a suitable template for drug development.

Target-Based Evaluation of "Drug-Like" Properties and Ligand Efficiencies

Physicochemical descriptors commonly used to define "drug-likeness" and ligand efficiency measures are assessed for their ability to differentiate marketed drugs from compounds reported to bind to their efficacious target or targets. Using ChEMBL version 26, a data set of 643 drugs acting on 271 targets was assembled, comprising 1104 drug-target pairs having ≥100 published compounds per target. Taking into account changes in their physicochemical properties over time, drugs are analyzed according to their target class, therapy area, and route of administration. Recent drugs, approved in 2010-2020, display no overall differences in molecular weight, lipophilicity, hydrogen bonding, or polar surface area from their target comparator compounds. Drugs are differentiated from target comparators by higher potency, ligand efficiency (LE), lipophilic ligand efficiency (LLE), and lower carboaromaticity. Overall, 96% of drugs have LE or LLE values, or both, greater than the median values of their target comparator compounds.

Fasted and fed state human duodenal fluids: Characterization, drug solubility, and comparison to simulated fluids and with human bioavailability

Accurate in vivo predictions of intestinal absorption of low solubility drugs require knowing their solubility in physiologically relevant dissolution media. Aspirated human intestinal fluids (HIF) are the gold standard, followed by simulated intestinal HIF in the fasted and fed state (FaSSIF/FeSSIF). However, current HIF characterization data vary, and there is also some controversy regarding the accuracy of FaSSIF and FeSSIF for predicting drug solubility in HIF. This study aimed at characterizing fasted and fed state duodenal HIF from 16 human volunteers with respect to pH, buffer capacity, osmolarity, surface tension, as well as protein, phospholipid, and bile salt content. The fasted and fed state HIF samples were further used to investigate the equilibrium solubility of 17 representative low-solubility small-molecule drugs, six of which were confidential industry compounds and 11 were known and characterized regarding chemical diversity. These solubility values were then compared to reported solubility values in fasted and fed state HIF, FaSSIF and FeSSIF, as well as with their human bioavailability for both states. The HIF compositions corresponded well to previously reported values and current FaSSIF and FeSSIF compositions. The drug solubility values in HIF (both fasted and fed states) were also well in line with reported solubility data for HIF, as well as simulated FaSSIF and FeSSIF. This indicates that the in vivo conditions in the proximal small intestine are well represented by simulated intestinal fluids in both composition and drug equilibrium solubility. However, increased drug solubility in the fed vs. fasted states in HIF did not correlate with the human bioavailability changes of the same drugs following oral administration in either state.

N,N′-dialkyl-2-thiobarbituric acid based sulfonamides as potential SARS-CoV-2 main protease inhibitors

An efficient methodology was developed to generate novel N,N′-dialkyl-2-thiobarbituric acid based sulfonamides S1–S4 in good to excellent yields (84%–95%). The synthesized compounds S1–S4 were docked to screen their in silico activities against two enzymes i.e., SARS-CoV-2 main protease enzyme with unliganded active site (2019-nCoV, coronavirus disease 2019, COVID-19) PDB ID: 6Y84 and SARS-CoV-2 Mpro PDB ID: 6LU7. Furthermore, some in silico physicochemical and physicokinetic properties were evaluated using the OSIRIS Property Explorer, Molinspiration property calculator, ADMET property calculator, and GUSAR to assess these compounds as potential candidates as lead compounds for the quest of SARS-CoV-2 main protease inhibitors. Molecular docking analyses of the synthesized compounds predicted that compound S3 is more potent as SARS-CoV-2 main protease inhibitor with binding energy –11.65 kcal/mol in comparison with reference inhibitor N3 (–10.95 kcal/mol), whereas compounds S1, S2, and S4 recorded comparable binding energies –9.89, –10.84, and –10.94 kcal/mol with reference inhibitor N3, which were much better than remdesivir (–9.85 kcal/mol). In case of SARS-CoV-2 Mpro, all compounds S1–S4 with docking energy values of –7.28, –8.38, –8.31, and –7.34 kcal/mol, respectively, were found to be potent in comparison with reference inhibitor N3 (–6.31 kcal/mol) and remdesivir (–6.33 kcal/mol). Ligand efficiency values against the target SARS-CoV-2 proteins, as well as α-glucosidase and DNA-(apurinic or apyrimidinic site) lyase inhibition results of these newly synthesized compounds, were also found to be promising.

Fragment-Based Nuclear Magnetic Resonance Screen against a Regulator of G Protein Signaling Identifies a Binding "Hot Spot"

Regulator of G protein signaling (RGS) proteins have attracted attention as a result of their primary role in directing the specificity as well as the temporal and spatial aspects of G protein-coupled receptor signaling. In addition, alterations in RGS protein expression have been observed in a number of disease states, including certain cancers. In this area, RGS17 is of particular interest. It has been demonstrated that, while RGS17 is expressed primarily in the central nervous system, it has been found to be inappropriately expressed in lung, prostate, breast, cervical, and hepatocellular carcinomas. Overexpression of RGS17 leads to dysfunction in inhibitory G protein signaling and an overproduction of the intracellular second messenger cAMP, which in turn alters the transcription patterns of proteins known to promote various cancer types. Suppressing RGS17 expression with RNA interference (RNAi) has been found to decrease tumorigenesis and sufficiently prevents cancer cell migration, leading to the hypothesis that pharmacological blocking of RGS17 function could be useful in anticancer therapies. We have identified small-molecule fragments capable of binding the RGS homology (RH) domain of RGS17 by using a nuclear magnetic resonance fragment-based screening approach. By chemical shift mapping of the two-dimensional ¹⁵ N,¹ H heteronuclear single quantum coherence (HSQC) spectra of the backbone-assigned ¹⁵ N-labeled RGS17-RH, we determined the fragment binding sites to be distant from the Gα interface. Thus, our study identifies a putative fragment binding site on RGS17 that was previously unknown.

Experimental and theoretical investigation of water-soluble silicon(IV) phthalocyanine and its interaction with bovine serum albumin

Photodynamic therapy (PDT) has drawn a great scientific attention to cancer treatment over the last decades. However, the bottleneck for the PDT is to find good photosensitizers (PSs) with greater water solubility, no aggregation, and fast discharge from the body. Therefore, there are still a big scientific desire for the synthesizing new rational PSs for treatment of cancer by PDT technique. In favor of improving the competence of PDT, an axially bis[4-(diphenylamino-1,1'-biphenyl-4-ol)] substituted silicon(IV) phthalocyanine (3) was converted to its water-soluble quaternized derivative (3Q). Their structures were fully characterized by single-crystal X-ray diffraction, elemental analysis, and different spectroscopic methods such as FT-IR, UV-Vis, MALDI-TOF, and ¹H-NMR. The photophysical properties such as fluorescence quantum yields and lifetimes, and the photochemical properties such as singlet oxygen generation of both phthalocyanines were investigated. Ground and excited-state calculations were performed to explain the observed electronic absorption spectra. The addition of the 4-diphenylamino-1,1'-biphenyl-4-ol groups on the axially positions of the silicon(IV) phthalocyanine increased the singlet oxygen quantum yield from 0.15 to around 0.20. Especially quaternized compound 3Q showed high singlet oxygen quantum yield of 0.26 in water solution. In addition, a spectroscopic investigation of the binding behavior of the quaternized silicon (IV) phthalocyanine complex to bovine serum albumin (BSA) is also studied in this work, confirming the possible interaction. Further theoretical calculations were carried out to find out the plausible-binding regions of the BSA protein. Axially bis[4-(diphenylamino-1,1'-biphenyl-4-ol)] substituted silicon(IV) phthalocyanine (3) was converted to its quaternized water soluble derivative (3Q). The photophysical properties such as fluorescence quantum yields and lifetimes, and the photochemical properties such as singlet oxygen generation of both phthalocyanines were investigated. In addition, a spectroscopic investigation of the binding behavior of the quaternized silicon (IV) phthalocyanine complex to bovine serum albumin (BSA) is also studied in this work, confirming the possible interaction. Further theoretical calculations were carried out to find out the plausible binding regions of the BSA protein.

Theoretical Evaluation of Novel Thermolysin Inhibitors from Bacillus thermoproteolyticus. Possible Antibacterial Agents

The search for new antibacterial agents that could decrease bacterial resistance is a subject in continuous development. Gram-negative and Gram-positive bacteria possess a group of metalloproteins belonging to the MEROPS peptidase (M4) family, which is the main virulence factor of these bacteria. In this work, we used the previous results of a computational biochemistry protocol of a series of ligands designed in silico using thermolysin as a model for the search of antihypertensive agents. Here, thermolysin from Bacillus thermoproteolyticus, a metalloprotein of the M4 family, was used to determine the most promising candidate as an antibacterial agent. Our results from docking, molecular dynamics simulation, molecular mechanics Poisson-Boltzmann (MM-PBSA) method, ligand efficiency, and ADME-Tox properties (Absorption, Distribution, Metabolism, Excretion, and Toxicity) indicate that the designed ligands were adequately oriented in the thermolysin active site. The Lig783, Lig2177, and Lig3444 compounds showed the best dynamic behavior; however, from the ADME-Tox calculated properties, Lig783 was selected as the unique antibacterial agent candidate amongst the designed ligands.

Design, synthesis and stepwise optimization of nitrile-based inhibitors of cathepsins B and L

Human cathepsin B (CatB) is an important biological target in cancer therapy. In this work, we performed a knowledge-based design approach and the synthesis of a new set of 19 peptide-like nitrile-based cathepsin inhibitors. Reported compounds were assayed against a panel of human cysteine proteases: CatB, CatL, CatK, and CatS. Three compounds (7h, 7i, and 7j) displayed nanomolar inhibition of CatB and selectivity over CatK and CatL. The selectivity was achieved by using the combination of a para biphenyl ring at P3, halogenated phenylalanine in P2 and Thr-O-Bz group at P1. Likewise, compounds 7i and 7j showed selective CatB inhibition among the panel of enzymes studied. We have also described a successful example of bioisosteric replacement of the amide bond for a sulfonamide one [7e → 6b], where we observed an increase in affinity and selectivity for CatB while lowering the compound lipophilicity (ilogP). Our knowledge-based design approach and the respective structure-activity relationships provide insights into the specific ligand-target interactions for therapeutically relevant cathepsins.

Intestinal absorption of BCS class II drugs administered as nanoparticles: A review based on in vivo data from intestinal perfusion models

An established pharmaceutical strategy to increase oral drug absorption of low solubility–high permeability drugs is to create nanoparticles of them. Reducing the size of the solid-state particles increases their dissolution and transport rate across the mucus barrier and the aqueous boundary layer. Suspensions of nanoparticles also sometimes behave differently than those of larger particles in the fed state. This review compares the absorption mechanisms of nano- and larger particles in the lumen at different prandial states, with an emphasis on data derived from in vivo models. Four BSC class II drugs—aprepitant, cyclosporine, danazol and fenofibrate—are discussed in detail based on information from preclinical intestinal perfusion models.

AMDock: a versatile graphical tool for assisting molecular docking with Autodock Vina and Autodock4

Abstract

AMDock (Assisted Molecular Docking) is a user-friendly graphical tool to assist in the docking of protein-ligand complexes using Autodock Vina and AutoDock4, including the option of using the Autodock4Zn force field for metalloproteins. AMDock integrates several external programs (Open Babel, PDB2PQR, AutoLigand, ADT scripts) to accurately prepare the input structure files and to optimally define the search space, offering several alternatives and different degrees of user supervision. For visualization of molecular structures, AMDock uses PyMOL, starting it automatically with several predefined visualization schemes to aid in setting up the box defining the search space and to visualize and analyze the docking results. One particularly useful feature implemented in AMDock is the off-target docking procedure that allows to conduct ligand selectivity studies easily. In summary, AMDock’s functional versatility makes it a very useful tool to conduct different docking studies, especially for beginners. The program is available, either for Windows or Linux, at https://github.com/Valdes-Tresanco-MS.

Reviewers

This article was reviewed by Alexander Krah and Thomas Gaillard.

Assessment of the Fragment Docking Program SEED

The fragment docking program solvation energy for exhaustive docking (SEED) is evaluated on 15 different protein targets, with a focus on enrichment and the hit rate. It is shown that SEED allows for consistent computational enrichment of fragment libraries, independent of the effective hit rate. Depending on the actual target protein, true positive rates ranging up to 27% are observed at a cutoff value corresponding to the experimental hit rate. The impact of variations in docking protocols and energy filters is discussed in detail. Remaining issues, limitations, and use cases of SEED are also discussed. Our results show that fragment library selection or enhancement for a particular target is likely to benefit from docking with SEED, suggesting that SEED is a useful resource for fragment screening campaigns. A workflow is presented for the use of the program in virtual screening, including filtering and postprocessing to optimize hit rates.

Designing novel inhibitors against cyclopropane mycolic acid synthase 3 (PcaA): targeting dormant state of Mycobacterium tuberculosis

Mycobacterium tuberculosis can sustain inside the host in dormant (non-replicating) state for years. It suppresses the host immune system by residing in the host alveolar macrophage, resulting in the development of latent tuberculosis. Despite many antibiotics available for the treatment of tuberculosis, the major hurdle in complete elimination is the ability of the bacilli to undergo dormancy and develop resistance against the existing drugs. Cyclopropanation of mycolic acids present in the cell wall of mycobacteria is required for its persistence and virulence. Cyclopropane synthases such as PcaA, CmaA1 and CmaA2, introduce site-specific modifications in mycolic acids. PcaA expression levels are high during dormancy and the gene mutants fails to persist, showing reduced survival in host macrophage. Hence, PcaA appears as a potential target to develop inhibitors against the dormant bacilli. In this study, we have identified compounds with maximum binding affinity against PcaA by in-silico virtual screening of anti-tuberculosis compounds and their structural analogues. In-silico docking followed molecular dynamic simulations and free energy calculations of the compounds with highest docking score in their respective libraries. This study reports novel inhibitors that can act as better anti-tuberculosis compounds targeting PcaA.Communicated by Ramaswamy H. Sarma.

Potential Inhibitors for Novel Coronavirus Protease Identified by Virtual Screening of 606 Million Compounds

The rapid outbreak of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China followed by its spread around the world poses a serious global concern for public health. To this date, no specific drugs or vaccines are available to treat SARS-CoV-2 despite its close relation to the SARS-CoV virus that caused a similar epidemic in 2003. Thus, there remains an urgent need for the identification and development of specific antiviral therapeutics against SARS-CoV-2. To conquer viral infections, the inhibition of proteases essential for proteolytic processing of viral polyproteins is a conventional therapeutic strategy. In order to find novel inhibitors, we computationally screened a compound library of over 606 million compounds for binding at the recently solved crystal structure of the main protease (Mpro) of SARS-CoV-2. A screening of such a vast chemical space for SARS-CoV-2 Mpro inhibitors has not been reported before. After shape screening, two docking protocols were applied followed by the determination of molecular descriptors relevant for pharmacokinetics to narrow down the number of initial hits. Next, molecular dynamics simulations were conducted to validate the stability of docked binding modes and comprehensively quantify ligand binding energies. After evaluation of potential off-target binding, we report a list of 12 purchasable compounds, with binding affinity to the target protease that is predicted to be more favorable than that of the cocrystallized peptidomimetic compound. In order to quickly advise ongoing therapeutic intervention for patients, we evaluated approved antiviral drugs and other protease inhibitors to provide a list of nine compounds for drug repurposing. Furthermore, we identified the natural compounds (-)-taxifolin and rhamnetin as potential inhibitors of Mpro. Rhamnetin is already commercially available in pharmacies.

STACKED - Solvation Theory of Aromatic Complexes as Key for Estimating Drug Binding

The use of fragments to biophysically characterize a protein binding pocket and determine the strengths of certain interactions is a computationally and experimentally commonly applied approach. Almost all drug like molecules contain at least one aromatic moiety forming stacking interactions in the binding pocket. In computational drug design, the strength of stacking and the resulting optimization of the aromatic core or moiety is usually calculated using high level quantum mechanical approaches. However, as these calculations are performed in a vacuum, solvation properties are neglected. We close this gap by using Grid Inhomogeneous Solvation Theory (GIST) to describe the properties of individual heteroaromatics and complexes and thereby estimate the desolvation penalty. In our study, we investigated the solvation free energies of heteroaromatics frequently occurring in drug design projects in complex with truncated side chains of phenylalanine, tyrosine, and tryptophan. Furthermore, we investigated the properties of drug-fragments crystallized in a fragment-based lead optimization approach investigating PDE-10-A. We do not only find good correlation for the estimated desolvation penalty and the experimental binding free energy, but our calculations also allow us to predict prominent interaction sites. We highlight the importance of including the desolvation penalty of the respective heteroaromatics in stacked complexes to explain the gain or loss in affinity of potential lead compounds.

Design, synthesis, biological evaluation and molecular modeling of novel 1H-pyrrolo[2,3-b]pyridine derivatives as potential anti-tumor agents

A class of 3-substituted 1H-pyrrolo[2,3-b]pyridine derivatives were designed, synthesized and evaluated for their in vitro biological activities against maternal embryonic leucine zipper kinase (MELK). Among these derivatives, the optimized compound 16h exhibited potent enzyme inhibition (IC₅₀ = 32 nM) and excellent anti-proliferative effect with IC₅₀ values from 0.109 μM to 0.245 μM on A549, MDA-MB-231 and MCF-7 cell lines. The results of flow cytometry indicated that 16h promoted apoptosis of A549 cells in a dose-dependent manner and effectively arrested A549 cells in the G0/G1 phase. Further investigation indicated that compound 16h potently suppressed the migration of A549 cells, had moderate stability in rat liver microsomes and showed moderate inhibitory activity against various subtypes of human cytochrome P450. However, compound 16h is a multi-target kinase inhibitor and recently several studies reported MELK expression is not required for cancer growth, suggesting that compound 16h suppressed the proliferation and migration of cancer cells should through an off-target mechanism. Collectively, compound 16h has the potential to serve as a new lead compound for further anticancer drug discovery.

Medicines discovery for auditory disorders: Challenges for industry

Currently, no approved medicines are available for the prevention or treatment of hearing loss. Pharmaceutical industry productivity across all therapeutic indications has historically been disappointing, with a 90% chance of failure in delivering a marketed drug after entering clinical evaluation. To address these failings, initiatives have been applied in the three cornerstones of medicine discovery: target selection, clinical candidate selection, and clinical studies. These changes aimed to enable data-informed decisions on the translation of preclinical observations into a safe, clinically effective medicine by ensuring the best biological target is selected, the most appropriate chemical entity is advanced, and that the clinical studies enroll the correct patients. The specific underlying pathologies need to be known to allow appropriate patient selection, so improved diagnostics are required, as are methodologies for measuring in the inner ear target engagement, drug delivery and pharmacokinetics. The different therapeutic strategies of protecting hearing or preventing hearing loss versus restoring hearing are reviewed along with potential treatments for tinnitus. Examples of current investigational drugs are discussed to highlight key challenges in drug discovery and the learnings being applied to improve the probability of success of launching a marketed medicine.

DockNmine, a Web Portal to Assemble and Analyse Virtual and Experimental Interaction Data

Scientists have to perform multiple experiments producing qualitative and quantitative data to determine if a compound is able to bind to a given target. Due to the large diversity of the potential ligand chemical space, the possibility of experimentally exploring a lot of compounds on a target rapidly becomes out of reach. Scientists therefore need to use virtual screening methods to determine the putative binding mode of ligands on a protein and then post-process the raw docking experiments with a dedicated scoring function in relation with experimental data. Two of the major difficulties for comparing docking predictions with experiments mostly come from the lack of transferability of experimental data and the lack of standardisation in molecule names. Although large portals like PubChem or ChEMBL are available for general purpose, there is no service allowing a formal expert annotation of both experimental data and docking studies. To address these issues, researchers build their own collection of data in flat files, often in spreadsheets, with limited possibilities of extensive annotations or standardisation of ligand descriptions allowing cross-database retrieval. We have conceived the dockNmine platform to provide a service allowing an expert and authenticated annotation of ligands and targets. First, this portal allows a scientist to incorporate controlled information in the database using reference identifiers for the protein (Uniprot ID) and the ligand (SMILES description), the data and the publication associated to it. Second, it allows the incorporation of docking experiments using forms that automatically parse useful parameters and results. Last, the web interface provides a lot of pre-computed outputs to assess the degree of correlations between docking experiments and experimental data.

Synthesis and structure-activity relationship of nitrile-based cruzain inhibitors incorporating a trifluoroethylamine-based P2 amide replacement

The structure-activity relationship for nitrile-based cruzain inhibitors incorporating a P2 amide replacement based on trifluoroethylamine was explored by deconstruction of a published series of inhibitors. It was demonstrated that the P3 biphenyl substituent present in the published inhibitor structures could be truncated to phenyl with only a small loss of affinity. The effects of inverting the configuration of the P2 amide replacement and linking a benzyl substituent at P1 were observed to be strongly nonadditive. We show that plotting affinity against molecular size provides a means to visualize both the molecular size efficiency of structural transformations and the nonadditivity in the structure-activity relationship. We also show how the relationship between affinity and lipophilicity, measured by high-performance liquid chromatography with an immobilized artificial membrane stationary phase, may be used to normalize affinity with respect to lipophilicity.