Complementarity between a docking and a high-throughput screen in discovering new cruzain inhibitors

ChemFH: an integrated tool for screening frequent false positives in chemical biology and drug discovery

High-throughput screening rapidly tests an extensive array of chemical compounds to identify hit compounds for specific biological targets in drug discovery. However, false-positive results disrupt hit compound screening, leading to wastage of time and resources. To address this, we propose ChemFH, an integrated online platform facilitating rapid virtual evaluation of potential false positives, including colloidal aggregators, spectroscopic interference compounds, firefly luciferase inhibitors, chemical reactive compounds, promiscuous compounds, and other assay interferences. By leveraging a dataset containing 823 391 compounds, we constructed high-quality prediction models using multi-task directed message-passing network (DMPNN) architectures combining uncertainty estimation, yielding an average AUC value of 0.91. Furthermore, ChemFH incorporated 1441 representative alert substructures derived from the collected data and ten commonly used frequent hitter screening rules. ChemFH was validated with an external set of 75 compounds. Subsequently, the virtual screening capability of ChemFH was successfully confirmed through its application to five virtual screening libraries. Furthermore, ChemFH underwent additional validation on two natural products and FDA-approved drugs, yielding reliable and accurate results. ChemFH is a comprehensive, reliable, and computationally efficient screening pipeline that facilitates the identification of true positive results in assays, contributing to enhanced efficiency and success rates in drug discovery. ChemFH is freely available via https://chemfh.scbdd.com/.

A structure-based virtual high-throughput screening, molecular docking, molecular dynamics and MM/PBSA study identified novel putative drug-like dual inhibitors of trypanosomal cruzain and rhodesain cysteine proteases

Virtual screening a collection of ~ 25,000 ChemBridge molecule collection identified two nitrogenous heterocyclic molecules, 12 and 15, with potential dual inhibitory properties against trypanosomal cruzain and rhodesain cysteine proteases. Similarity search in DrugBank found the two virtual hits with novel chemical structures with unreported anti-trypanosomal activities. Investigations into the binding mechanism by molecular dynamics simulations for 100 ns revealed the molecules were able to occupy the binding sites and stabilise the protease complexes. Binding affinities calculated using the MM/PBSA method for the last 20 ns showed that the virtual hits have comparable binding affinities to other known inhibitors from literature suggesting both molecules as promising scaffolds with dual cruzain and rhodesain inhibition properties, i.e. 12 has predicted ΔGbind values of - 38.1 and - 38.2 kcal/mol to cruzain and rhodesain, respectively, and 15 has predicted ΔGbind values of - 34.4 and - 25.8 kcal/mol to rhodesain. Per residue binding free energy decomposition studies and visual inspection at 100 ns snapshots revealed hydrogen bonding and non-polar attractions with important amino acid residues that contributed to the ΔGbind values. The interactions are similar to those previously reported in the literature. The overall ADMET predictions for the two molecules were favourable for drug development with acceptable pharmacokinetic profiles and adequate oral bioavailability.

Integrated Computational Approaches for Drug Design Targeting Cruzipain

Cruzipain inhibitors are required after medications to treat Chagas disease because of the need for safer, more effective treatments. Trypanosoma cruzi is the source of cruzipain, a crucial cysteine protease that has driven interest in using computational methods to create more effective inhibitors. We employed a 3D-QSAR model, using a dataset of 36 known inhibitors, and a pharmacophore model to identify potential inhibitors for cruzipain. We also built a deep learning model using the Deep purpose library, trained on 204 active compounds, and validated it with a specific test set. During a comprehensive screening of the Drug Bank database of 8533 molecules, pharmacophore and deep learning models identified 1012 and 340 drug-like molecules, respectively. These molecules were further evaluated through molecular docking, followed by induced-fit docking. Ultimately, molecular dynamics simulation was performed for the final potent inhibitors that exhibited strong binding interactions. These results present four novel cruzipain inhibitors that can inhibit the cruzipain protein of T. cruzi.

Target-based drug design strategies to overcome resistance to antiviral agents: opportunities and challenges

Viral infections have a major impact in human health. Ongoing viral transmission and escalating selective pressure have the potential to favor the emergence of vaccine- and antiviral drug-resistant viruses. Target-based approaches for the design of antiviral drugs can play a pivotal role in combating drug-resistant challenges. Drug design computational tools facilitate the discovery of novel drugs. This review provides a comprehensive overview of current drug design strategies employed in the field of antiviral drug resistance, illustrated through the description of a series of successful applications. These strategies include technologies that enhance compound-target affinity while minimizing interactions with mutated binding pockets. Furthermore, emerging approaches such as virtual screening, targeted protein/RNA degradation, and resistance analysis during drug design have been harnessed to curtail the emergence of drug resistance. Additionally, host targeting antiviral drugs offer a promising avenue for circumventing viral mutation. The widespread adoption of these refined drug design strategies will effectively address the prevailing challenge posed by antiviral drug resistance.

Structure-activity relationships of novel N-imidazoylpiperazines with potent anti-Trypanosoma cruzi activity

Background: Chagas disease is caused by the parasite Trypanosoma cruzi, and the lack of effective and safe treatments makes identifying new classes of compounds with anti-T. cruzi activity of paramount importance. Methods: Hit-to-lead exploration of a metabolically stable N-imidazoylpiperazine was performed. Results: Compound 2, a piperazine derivative active against T. cruzi, was selected to perform the hit-to-lead exploration, which involved the design, synthesis and biological evaluation of 39 new derivatives. Conclusion: Compounds 6e and 10a were identified as optimized compounds with low micromolar in vitro activity, low cytotoxicity and suitable preliminary absorption, distribution, metabolism and excretion and physicochemical properties. Both compounds reduced parasitemia in mouse models of Chagas disease, providing a promising opportunity for further exploration of new antichagasic compounds.

Drug Discovery Efforts to Identify Novel Treatments for Neglected Tropical Diseases - Cysteine Protease Inhibitors

BACKGROUND

Neglected tropical diseases are a severe burden for mankind, affecting an increasing number of people around the globe. Many of those diseases are caused by protozoan parasites in which cysteine proteases play a key role in the parasite's pathogenesis.

OBJECTIVE

In this review article, we summarize the drug discovery efforts of the research community from 2017 - 2022 with a special focus on the optimization of small molecule cysteine protease inhibitors in terms of selectivity profiles or drug-like properties as well as in vivo studies. The cysteine proteases evaluated by this methodology include Cathepsin B1 from Schistosoma mansoni, papain, cruzain, falcipain, and rhodesain.

METHODS

Exhaustive literature searches were performed using the keywords "Cysteine Proteases" and "Neglected Tropical Diseases" including the years 2017 - 2022. Overall, approximately 3'000 scientific papers were retrieved, which were filtered using specific keywords enabling the focus on drug discovery efforts.

RESULTS AND CONCLUSION

Potent and selective cysteine protease inhibitors to treat neglected tropical diseases were identified, which progressed to pharmacokinetic and in vivo efficacy studies. As far as the authors are aware of, none of those inhibitors reached the stage of active clinical development. Either the inhibitor's potency or pharmacokinetic properties or safety profile or a combination thereof prevented further development of the compounds. More efforts with particular emphasis on optimizing pharmacokinetic and safety properties are needed, potentially by collaborations of academic and industrial research groups with complementary expertise. Furthermore, new warheads reacting with the catalytic cysteine should be exploited to advance the research field in order to make a meaningful impact on society.

Unraveling the unexpected aggregation behavior of Pyrazole-Based compounds Targeting Mycobacterium tuberculosis UDP-Galactopyranose mutase

A pyrazole-based compound, MS208, was previously identified as an inhibitor of UDP-Galactopyranose Mutase from Mycobacterium tuberculosis (MtUGM). Targeting this enzyme is a novel therapeutic strategy for the development of new antituberculosis agents because MtUGM is an essential enzyme for the bacterial cell wall synthesis and it is not present in human. It was proposed that MS208 targets an allosteric site in MtUGM as MS208 followed a mixed inhibition model. DA10, an MS208 analogue, showed competitive inhibition rather than mixed inhibition. In this paper, we have used an integrated biophysical approach, including thermal shift assays, dynamic light scattering and nuclear magnetic resonance experiments, to show that MS208 and many analogues displayed unexpected aggregation behavior against MtUGM.

Convergent QSAR Models for the Prediction of Cruzain Inhibitors

Chagas disease is a parasitosis caused by Trypanosoma cruzi. Cruzain, the major cysteine protease from T. cruzi, is an excellent therapeutic target in the search for antichagasic drugs. It is important in the role of cell invasion, replication, differentiation, and metabolism of the parasite. In this work, we developed and assessed multiple quantitative structure-activity relationship (QSAR) models for a set of 61 cruzain inhibitors. These models include two-dimensional (2D) QSAR, three-dimensional (3D) QSAR, such as comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), and Hologram QSAR (HQSAR). In total, we generated 10 major and 114 minor model variations. Molecular docking was used to successfully align the molecules. All CoMFA and CoMSIA models, which incorporate multiple fields, demonstrated robustness in our analysis. Steric fields exhibited satisfactory convergence in the contour maps, while the electrostatic field converged into a single small region. The HQSAR model taking into consideration only Atoms and Connectivity, with fragment sizes ranging from two to five atoms, was considered the best of the HQSAR variations, despite exhibiting a higher level of deviance. In total, 78 model variations meet the minimum requirements to be considered acceptable. We found that using as few as five descriptors it is possible to obtain robust results with 2D-QSAR. Models such as Random Forest, Tree Ensemble, Linear Regression, and HQSAR are recommended for working with large data sets, while the 3D-QSAR models are intended to study the geometry of the ligands, to optimize them into new and better performing antichagasics. Virtual Screening of a set of hydrazones, guided by the top-performing models, identified promising candidates for experimental validation. Among them, dv007 and dv015 exhibited consistently high predicted pIC50 values (7.26 and 7.24, respectively), making them compelling candidates for further drug development.

Molecular targets for Chagas disease: validation, challenges and lead compounds for widely exploited targets

INTRODUCTION

Chagas disease (CD) imposes social and economic burdens, yet the available treatments have limited efficacy in the disease's chronic phase and cause serious adverse effects. To address this challenge, target-based approaches are a possible strategy to develop new, safe, and active treatments for both phases of the disease.

AREAS COVERED

This review delves into target-based approaches applied to CD drug discovery, emphasizing the studies from the last five years. We highlight the proteins cruzain (CZ), trypanothione reductase (TR), sterol 14 α-demethylase (CPY51), iron superoxide dismutase (Fe-SOD), proteasome, cytochrome b (Cytb), and cleavage and polyadenylation specificity factor 3 (CPSF3), chosen based on their biological and chemical validation as drug targets. For each, we discuss its biological relevance and validation as a target, currently related challenges, and the status of the most promising inhibitors.

EXPERT OPINION

Target-based approaches toward developing potential CD therapeutics have yielded promising leads in recent years. We expect a significant advance in this field in the next decade, fueled by the new options for Trypanosoma cruzi genetic manipulation that arose in the past decade, combined with recent advances in computational chemistry and chemical biology.

Structure-based discovery of novel cruzain inhibitors with distinct trypanocidal activity profiles

Over 110 years after the first formal description of Chagas disease, the trypanocidal drugs thus far available have limited efficacy and several side effects. This encourages the search for novel treatments that inhibit T. cruzi targets. One of the most studied anti-T. cruzi targets is the cysteine protease cruzain; it is associated with metacyclogenesis, replication, and invasion of the host cells. We used computational techniques to identify novel molecular scaffolds that act as cruzain inhibitors. First, with a docking-based virtual screening, we identified compound 8, a competitive cruzain inhibitor with a K_i of 4.6 μM. Then, aided by molecular dynamics simulations, cheminformatics, and docking, we identified the analog compound 22 with a K_i of 27 μM. Surprisingly, despite sharing the same isoquinoline scaffold, compound 8 presented higher trypanocidal activity against the epimastigote forms, while compound 22, against the trypomastigotes and amastigotes. Taken together, compounds 8 and 22 represent a promising scaffold for further development of trypanocidal compounds as drug candidates for treating Chagas disease.

Design, synthesis and biological evaluation of novel thiosemicarbazones as cruzipain inhibitors

Based on the activity of 23 TSCs on CZ taken from the literature, we have developed a QSAR model for predicting the activity of TSCs. New TSCs were designed and then tested against CZP, resulting in inhibitors with IC₅₀ values in the nanomolar range. The modelling of the corresponding TSC-CZ complexes by molecular docking and QM/QM ONIOM refinement indicates a binding mode compatible with what was expected for active TSCs, according to a geometry-based theoretical model previously developed by our research group. Kinetic experiments on CZP suggest that the new TSCs act by a mechanism that involves the formation of a reversible covalent adduct with slow association and dissociation kinetics. These results demonstrate the strong inhibitory effect of the new TSCs and the benefit of the combined use of QSAR and molecular modelling techniques in the design of new and potent CZ/CZP inhibitors.

Next-generation intelligent laboratories for materials design and manufacturing

The contradiction between the importance of materials to modern society and their slow development process has led to the development of multiple methods to accelerate materials discovery. The recently emerged concept of intelligent laboratories integrates the developments in fields of high-throughput experimentation, automation, theoretical computing, and artificial intelligence to form a system that can autonomously carry out designed experiments and make scientific discoveries. We present the basic concepts and the foundations of this new research paradigm, demonstrate its typical application scenarios through case studies, and envision a collaborative human-machine meta laboratory in the future.

Identification of inhibitors as drug candidates against Chagas disease

Chagas disease, after more than a century after its discovery, is still a major public health problem. It is estimated that approximately 10 million people worldwide are infected with T. cruzi. However, the situation is more critical in Latin America and other regions where the disease is endemic. The largest number of cases occurs in Brazil, Argentina, and Mexico as more than 100 million people in these regions are located in areas with a high risk of contamination by the vector. The need for new therapeutic alternatives is urgent, as the available drugs have severe limitations such as low efficacy and high toxicity. From this scenario, in this work, we employed the virtual screening technique using cruzain and BDF2 as key biological targets for the survival of the parasite. Our objective was to identify potential inhibitors of T. cruzi trypomastigotes, which could be considered drug candidates against Chagas disease. For this, we employed different in silico methodologies and the obtained results were corroborated using in vitro biological assays. For the VS studies, a database containing synthetic compounds was simulated at the binding site of cruzain and BDF2. In addition, pharmacophoric models were constructed in the initial phases of VS, as well as other advanced analyses (molecular dynamics simulations, calculations of binding free energy, and ADME prediction) were carried out and the results allowed the selection of potential inhibitors of T. cruzi. Based on the obtained data, 32 different compounds commercially available were subjected to biological tests against the trypomastigote form of T. cruzi. As result, 11 of those compounds displayed significant activity against T. cruzi and can be considered potential candidates for the treatment of Chagas disease.

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.

The Mechanisms Underlying the Pharmacological Effects of GuiPi Decoction on Major Depressive Disorder based on Network Pharmacology and Molecular Docking

BACKGROUND AND AIM

Major Depressive Disorder (MDD) is a common affective disorder. GuiPi decoction (GPD) is used to treat depression in China, Japan, and Korea. However, its effective ingredients and antidepressant mechanisms remain unclear. We attempted to reveal the potential mechanisms of GPD in the treatment of MDD by network pharmacology and molecular docking. In addition, we conducted an enzymatic activity assay to validate the results of molecular docking.

METHODS

GPD-related compounds and targets, and MDD-related targets were retrieved from databases and literature. The herb-compound-target network was constructed by Cytoscape. The protein- protein interaction network was built using the STRING database to find key targets of GPD on MDD. Enrichment analysis of shared targets was analyzed by MetaCore database to obtain the potential pathway and biological process of GPD on MDD. The main active compounds treating MDD were screened by molecular docking. The PDE4s inhibitors were screened and verified by an enzyme activity assay.

RESULTS

GPD contained 1222 ingredients and 190 potential targets for anti-MDD. Possible biological processes regulated by GPD were neurophysiological processes, blood vessel morphogenesis, Camp Responsive Element Modulator (CREM) pathway, and Androgen Receptor (AR) signaling crosstalk in MDD. Potential pathways in MDD associated with GPD include neurotransmission, cell differentiation, androgen signaling, and estrogen signaling. Fumarine, m-cresol, quercetin, betasitosterol, fumarine, taraxasterol, and lupeol in GPD may be the targets of SLC6A4, monoamine oxidase A (MAOA), DRD2, OPRM1, HTR3A, Albumin (ALB), and NTRK1, respectively. The IC50 values of trifolin targeting Phosphodiesterase (PDE) 4A and girinimbine targeting PDE4B1 were 73.79 μM and 31.86 μM, respectively. The IC50 values of girinimbine and benzo[a]carbazole on PDE4B2 were 51.62 μM and 94.61 μM, respectively.

CONCLUSION

Different compounds in GPD may target the same protein, and the same component in GPD can target multiple targets. These results suggest that the effects of GPD on MDD are holistic and systematic, unlike the pattern of one drug-one target.

Discovery of pulmonary fibrosis inhibitor targeting TGF-β RI in Polygonum cuspidatum by high resolution mass spectrometry with in silico strategy

Pulmonary fibrosis (PF) is an irreversible lung disease that is characterized by excessive scar tissue with a poor median survival rate of 2-3 years. The inhibition of transforming growth factor-β receptor type-I (TGF-β RI) by an appropriate drug may provide a promising strategy for the treatment of this disease. Polygonum cuspidatum (PC) is a well-known traditional Chinese herbal medicine which has an anti-PF effect. Accordingly, a combination of high resolution mass spectrometry with an in silico strategy was developed as a new method to search for potential chemical ingredients of PC that target the TGF-β RI. Based on this strategy, a total of 24 ingredients were identified. Then, absorption, distribution, metabolism, and excretion (ADME)-related properties were subsequently predicted to exclude compounds with potentially undesirable pharmacokinetics behaviour. Molecular docking studies on TGF-β RI were adopted to discover new PF inhibitors. Eventually, a compound that exists in PC known as resveratrol was proven to have excellent biological activity on TGF-β RI, with an IC₅₀ of 2.211 μM in vitro. Furthermore, the complex formed through molecular docking was tested via molecular dynamics simulations, which revealed that resveratrol had strong interactions with residues of TGF-β RI. This study revealed that resveratrol has significant potential as a treatment for PF due to its ability to target TGF-β RI. In addition, this research demonstrated the exploration of natural products with excellent biological activities toward specific targets via high resolution mass spectrometry in combination with in silico technology is a promising strategy for the discovery of novel drugs.

Integrating transcriptomics and network analysis-based multiplexed drug repurposing to screen drug candidates for M2 macrophage-associated castration-resistant prostate cancer bone metastases

Metastatic castration-resistant prostate cancer (CRPC) has long been considered to be associated with patient mortality. Among metastatic organs, bone is the most common metastatic site, with more than 90% of advanced patients developing bone metastases (BMs) before 24 months of death. Although patients were recommended to use bone-targeted drugs represented by bisphosphonates to treat BMs of CRPC, there was no significant improvement in patient survival. In addition, the use of immunotherapy and androgen deprivation therapy is limited due to the immunosuppressed state and resistance to antiandrogen agents in patients with bone metastases. Therefore, it is still essential to develop a safe and effective therapeutic schedule for CRPC patients with BMs. To this end, we propose a multiplex drug repurposing scheme targeting differences in patient immune cell composition. The identified drug candidates were ranked from the perspective of M2 macrophages by integrating transcriptome and network-based analysis. Meanwhile, computational chemistry and clinical trials were used to generate a comprehensive drug candidate list for the BMs of CRPC by drug redundancy structure filtering. In addition to docetaxel, which has been approved for clinical trials, the list includes norethindrone, testosterone, menthol and foretinib. This study provides a new scheme for BMs of CRPC from the perspective of M2 macrophages. It is undeniable that this multiplex drug repurposing scheme specifically for immune cell-related bone metastases can be used for drug screening of any immune-related disease, helping clinicians find promising therapeutic schedules more quickly, and providing reference information for drug R&D and clinical trials.

De Novo Design of Cathepsin B1 Inhibitors as Potential Anti-Schistosomal Agents Using Computational Studies

Background

Schistosomiasis is the world’s second most devastating disease after malaria and the leading cause of disease and mortality for more than 200 million people in developing countries. Cysteine proteases, in particular SmCB1, are the most well-researched biological targets for this disorder.

Objective

To apply computational techniques to design new antischistosomal agents against SmCB1 protein with favorable pharmacokinetic properties.

Methods

The smCB1 receptor-based pharmacophore model was created and used to screen 567,000 fragments from the Enamine library. The best scoring fragments have been linked to build novel compounds that were subjected to molecular docking, MM-GBSA free energy estimation, ADME prediction, and molecular dynamics.

Results

A seven-point pharmacophore hypothesis ADDDRRR was created. The developed hypothesis was used to screen 1.3 M fragment conformations. Among them, 23,732 fragments matched the hypothesis and screened against the protein. The top 50 fragments were used to design new 7745 compounds using the Breed ligand panel which were subjected to docking and MMGBSA binding energy. This led to the identification of 10 compounds with better docking scores (−8.033– −7.483 kcal/mol) and lower-bound free energies (−58.49 – −40.02 kcal/mol) compared to the reference bound ligand. Most of the designed compounds demonstrated good drug-like properties. Concerning Molecular dynamics (MD) simulation results, a low root mean square deviation (RMSD) range (0.25–1.2 Å) was found for the top 3 complexes which indicated their stability.

Conclusion

We identified compounds that could be potential candidates in the search for novel Schistosoma mansoni inhibitors by targeting SmCB1 utilizing various computational tools. Three newly designed compounds namely breed 1, 2, and 3 showed promising affinity to the target as well as favorable drug-like properties which might be considered potential anti-schistosomal agents.

Essential Dynamics Ensemble Docking for Structure-Based GPCR Drug Discovery

The lack of biologically relevant protein structures can hinder rational design of small molecules to target G protein-coupled receptors (GPCRs). While ensemble docking using multiple models of the protein target is a promising technique for structure-based drug discovery, model clustering and selection still need further investigations to achieve both high accuracy and efficiency. In this work, we have developed an original ensemble docking approach, which identifies the most relevant conformations based on the essential dynamics of the protein pocket. This approach is applied to the study of small-molecule antagonists for the PAC1 receptor, a class B GPCR and a regulator of stress. As few as four representative PAC1 models are selected from simulations of a homology model and then used to screen three million compounds from the ZINC database and 23 experimentally validated compounds for PAC1 targeting. Our essential dynamics ensemble docking (EDED) approach can effectively reduce the number of false negatives in virtual screening and improve the accuracy to seek potent compounds. Given the cost and difficulties to determine membrane protein structures for all the relevant states, our methodology can be useful for future discovery of small molecules to target more other GPCRs, either with or without experimental structures.

Maximizing the integration of virtual and experimental screening in hit discovery

INTRODUCTION

Experimental and virtual screening contributes to the discovery of more than 50% of clinical candidates. Considering the similar concept and goals, early-phase drug discovery would benefit from the effective integration of these approaches.

AREAS COVERED

After reviewing the recent trends in both experimental and virtual screening, the authors discuss different integration strategies from parallel, focused, sequential, and iterative screening. Strategic considerations are demonstrated in a number of real-life case studies.

EXPERT OPINION

Experimental and virtual screening are complementary approaches that should be integrated in lead discovery settings. Virtual screening can access extremely large synthetically feasible chemical space that can be effectively searched on GPU clusters or cloud architectures. Experimental screening provides reliable datasets by quantitative HTS applications, and DNA-encoded libraries (DEL) have enlarged the chemical space covered by these technologies. These developments, together with the use of artificial intelligence methods, represent new options for their efficient integration. The case studies discussed here demonstrate the benefits of complementary strategies, such as focused and iterative screening.

The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice

In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.

Natural Compound ZINC12899676 Reduces Porcine Epidemic Diarrhea Virus Replication by Inhibiting the Viral NTPase Activity

Porcine epidemic diarrhea virus (PEDV) is an alphacoronavirus (α-CoV) that causes high mortality in suckling piglets, leading to severe economic losses worldwide. No effective vaccine or commercial antiviral drug is readily available. Several replicative enzymes are responsible for coronavirus replication. In this study, the potential candidates targeting replicative enzymes (PLP2, 3CLpro, RdRp, NTPase, and NendoU) were screened from 187,119 compounds in ZINC natural products library, and seven compounds had high binding potential to NTPase and showed drug-like property. Among them, ZINC12899676 was identified to significantly inhibit the NTPase activity of PEDV by targeting its active pocket and causing its conformational change, and ZINC12899676 significantly inhibited PEDV replication in IPEC-J2 cells. It first demonstrated that ZINC12899676 inhibits PEDV replication by targeting NTPase, and then, NTPase may serve as a novel target for anti-PEDV.

Study of the dynamic behavior of the cruzain enzyme in free and complexed forms with competitive and noncovalent benzimidazole inhibitors

There are only two drugs for the treatment of Chagas disease, namely, nifurtimox and benznidazole, that can cause several adverse effects. Despite the effectiveness of these drugs in the disease's acute phase, they are not recognized as curative in the chronic phase, establishing the need for more effective treatment in all stages of the disease. Cruzain is an enzyme that plays a vital role in the life cycle of the etiologic agent, the protozoan Trypanosoma cruzi, being relevant as a therapeutic target in the planning of new drugs. Using molecular docking and dynamics simulations, we have investigated the structural and dynamic factors that can be involved in the enzyme inhibition process at the atomic-molecular level by benzimidazole compounds that are potent cruzain inhibitors with in vitro trypanocidal activity. The study suggests that these inhibitors bind cruzain through steric and hydrogen bonding interactions without altering its secondary structure content and protein compaction. Besides, we observed that these inhibitors decrease the correlation of movements between Cα-atoms of cruzain, increasing the number of atomic communities, mainly in the α-helix that presents the catalytic Cys25 residue. As expected, we also observed a correlation between the inhibitory activity of each inhibitor and their respective binding-free energies, reinforcing that the affinity of the complexes seems to be a relevant factor for enzymatic inhibition. Hence, the results presented in this work contribute to a better understanding of the cruzain enzyme inhibition mechanism through competitive and non-covalent inhibitors.Communicated by Ramaswamy H. Sarma.

Isometric Stratified Ensembles: A Partial and Incremental Adaptive Applicability Domain and Consensus-Based Classification Strategy for Highly Imbalanced Data Sets with Application to Colloidal Aggregation

Partial and incremental stratification analysis of a quantitative structure-interference relationship (QSIR) is a novel strategy intended to categorize classification provided by machine learning techniques. It is based on a 2D mapping of classification statistics onto two categorical axes: the degree of consensus and level of applicability domain. An internal cross-validation set allows to determine the statistical performance of the ensemble at every 2D map stratum and hence to define isometric local performance regions with the aim of better hit ranking and selection. During training, isometric stratified ensembles (ISE) applies a recursive decorrelated variable selection and considers the cardinal ratio of classes to balance training sets and thus avoid bias due to possible class imbalance. To exemplify the interest of this strategy, three different highly imbalanced PubChem pairs of AmpC β-lactamase and cruzain inhibition assay campaigns of colloidal aggregators and complementary aggregators data set available at the AGGREGATOR ADVISOR predictor web page were employed. Statistics obtained using this new strategy show outperforming results compared to former published tools, with and without a classical applicability domain. ISE performance on classifying colloidal aggregators shows from a global AUC of 0.82, when the whole test data set is considered, up to a maximum AUC of 0.88, when its highest confidence isometric stratum is retained.

Multiparameter Optimization of Trypanocidal Cruzain Inhibitors With In Vivo Activity and Favorable Pharmacokinetics

Cruzain, the main cysteine protease of Trypanosoma cruzi, plays key roles in all stages of the parasite's life cycle, including nutrition acquisition, differentiation, evasion of the host immune system, and invasion of host cells. Thus, inhibition of this validated target may lead to the development of novel drugs for the treatment of Chagas disease. In this study, a multiparameter optimization (MPO) approach, molecular modeling, and structure-activity relationships (SARs) were employed for the identification of new benzimidazole derivatives as potent competitive inhibitors of cruzain with trypanocidal activity and suitable pharmacokinetics. Extensive pharmacokinetic studies enabled the identification of metabolically stable and permeable compounds with high selectivity indices. CYP3A4 was found to be involved in the main metabolic pathway, and the identification of metabolic soft spots provided insights into molecular optimization. Compound 28, which showed a promising trade-off between pharmacodynamics and pharmacokinetics, caused no acute toxicity and reduced parasite burden both in vitro and in vivo.

Virtual Screening Directly Identifies New Fragment-Sized Inhibitors of Carboxylesterase Notum with Nanomolar Activity

Notum is a negative regulator of Wnt signaling acting through the hydrolysis of a palmitoleoylate ester, which is required for Wnt activity. Inhibitors of Notum could be of use in diseases where dysfunctional Notum activity is an underlying cause. A docking-based virtual screen (VS) of a large commercial library was used to shortlist 952 compounds for experimental validation as inhibitors of Notum. The VS was successful with 31 compounds having an IC50 < 500 nM. A critical selection process was then applied with two clusters and two singletons (1-4d) selected for hit validation. Optimization of 4d guided by structural biology identified potent inhibitors of Notum activity that restored Wnt/β-catenin signaling in cell-based models. The [1,2,4]triazolo[4,3-b]pyradizin-3(2H)-one series 4 represent a new chemical class of Notum inhibitors and the first to be discovered by a VS campaign. These results demonstrate the value of VS with well-designed docking models based on X-ray structures.

Impact of different protonation states on virtual screening performance against cruzain

The cysteine protease cruzain is a Chagas disease target, exploited in computational studies. However, there is no consensus on the protonation states of the active site residues Cys25, His162, and Glu208 at the enzyme's active pH range. We evaluated the impact of different protonation states of these residues on docking calculations. Through a retrospective study with cruzain inhibitors and decoys, we compared the performance of virtual screening using four grids, varying protonation states of Cys25, His162, and Glu208. Based on enrichment factors and ROC plots, docking with the four grids affected compound ranking and the overall charge of top-ranking compounds. Different grids can be complementary and synergistic, increasing the odds of finding different ligands with diverse chemical properties.

Cross-Platform Bayesian Optimization System for Autonomous Biological Assay Development

Current high-throughput screening assay optimization is often a manual and time-consuming process, even when utilizing design-of-experiment approaches. A cross-platform, Cloud-based Bayesian optimization-based algorithm was developed as part of the National Center for Advancing Translational Sciences (NCATS) ASPIRE (A Specialized Platform for Innovative Research Exploration) Initiative to accelerate preclinical drug discovery. A cell-free assay for papain enzymatic activity was used as proof of concept for biological assay development and system operationalization. Compared with a brute-force approach that sequentially tested all 294 assay conditions to find the global optimum, the Bayesian optimization algorithm could find suitable conditions for optimal assay performance by testing 21 assay conditions on average, with up to 20 conditions being tested simultaneously, as confirmed by repeated simulation. The algorithm could achieve a sevenfold reduction in costs for lab supplies and high-throughput experimentation runtime, all while being controlled from a remote site through a secure connection. Based on this proof of concept, this technology is expected to be applied to more complex biological assays and automated chemistry reaction screening at NCATS, and should be transferable to other institutions.

Cardiac ryanodine receptor N-terminal region biosensors identify novel inhibitors via FRET-based high-throughput screening

The N-terminal region (NTR) of ryanodine receptor (RyR) channels is critical for the regulation of Ca²⁺ release during excitation–contraction (EC) coupling in muscle. The NTR hosts numerous mutations linked to skeletal (RyR1) and cardiac (RyR2) myopathies, highlighting its potential as a therapeutic target. Here, we constructed two biosensors by labeling the mouse RyR2 NTR at domains A, B, and C with FRET pairs. Using fluorescence lifetime (FLT) detection of intramolecular FRET signal, we developed high-throughput screening (HTS) assays with these biosensors to identify small-molecule RyR modulators. We then screened a small validation library and identified several hits. Hits with saturable FRET dose–response profiles and previously unreported effects on RyR were further tested using [³H]ryanodine binding to isolated sarcoplasmic reticulum vesicles to determine effects on intact RyR opening in its natural membrane. We identified three novel inhibitors of both RyR1 and RyR2 and two RyR1-selective inhibitors effective at nanomolar Ca²⁺. Two of these hits activated RyR1 only at micromolar Ca²⁺, highlighting them as potential enhancers of excitation–contraction coupling. To determine whether such hits can inhibit RyR leak in muscle, we further focused on one, an FDA-approved natural antibiotic, fusidic acid (FA). In skinned skeletal myofibers and permeabilized cardiomyocytes, FA inhibited RyR leak with no detrimental effect on skeletal myofiber excitation–contraction coupling. However, in intact cardiomyocytes, FA induced arrhythmogenic Ca²⁺ transients, a cautionary observation for a compound with an otherwise solid safety record. These results indicate that HTS campaigns using the NTR biosensor can identify compounds with therapeutic potential.

Diaminomaleonitrile derivatives as new potential antichagasic compounds: a study of structure-activity relationships

Background: Schiff bases are synthetically accessible compounds that have been used in medicinal chemistry. Methods & results: In this work, 27 Schiff bases derived from diaminomaleonitrile were synthesized in high yields (80-98%). Molecular docking studies suggested that the Schiff bases interact with the catalytic site of cruzain. The most active cruzain inhibitor, analog 13 (IC₅₀ = 263 nM), was predicted to form an additional hydrophobic contact with Met68 in the binding site of the enzyme. A strong correlation between the IC₅₀ values and ChemScore binding energies was observed (R = 0.99). Kernel-based 2D quantitative structure-activity relationship models for the whole dataset yielded sound correlation coefficients (R² = 0.844; Q² = 0.719). Conclusion: These novel and potent cruzain inhibitors are worthwhile starting points in further Chagas disease drug discovery programs.

Cysteine proteases as potential targets for anti-trypanosomatid drug discovery

Leishmaniasis and trypanosomiasis are endemic neglected disease in South America and Africa and considered a significant public health problem, mainly in poor communities. The limitations of the current available therapeutic options, including the lack of specificity, relatively high toxicity, and the drug resistance acquiring, drive the constant search for new targets and therapeutic options. Advances in knowledge of parasite biology have revealed essential enzymes involved in the replication, survival, and pathogenicity of Leishmania and Trypanosoma species. In this scenario, cysteine proteases have drawn the attention of researchers and they are being proposed as promising targets for drug discovery of antiprotozoal drugs. In this systematic review, we will provide an update on drug discovery strategies targeting the cysteine proteases as potential targets for chemotherapy against protozoal neglected diseases.

Structure-Based Optimization of Quinazolines as Cruzain and TbrCATL Inhibitors

The cysteine proteases, cruzain and TbrCATL (rhodesain), are therapeutic targets for Chagas disease and Human African Trypanosomiasis, respectively. Among the known inhibitors for these proteases, we have described N⁴-benzyl-N²-phenylquinazoline-2,4-diamine (compound 7 in the original publication, 1a in this study), as a competitive cruzain inhibitor (K_i = 1.4 μM). Here, we describe the synthesis and biological evaluation of 22 analogs of 1a, containing modifications in the quinazoline core, and in the substituents in positions 2 and 4 of this ring. The analogs demonstrate low micromolar inhibition of the target proteases and cidal activity against Trypanosoma cruzi with up to two log selectivity indices in counterscreens with myoblasts. Fourteen compounds were active against Trypanosoma brucei at low to mid micromolar concentrations. During the optimization of 1a, structure-based design and prediction of physicochemical properties were employed to maintain potency against the enzymes while removing colloidal aggregator characteristics observed for some molecules in this series.

Repurposing Carvedilol as a Novel Inhibitor of the Trypanosoma cruzi Autophagy Flux That Affects Parasite Replication and Survival

T. cruzi, the causal agent of Chagas disease, is a parasite able to infect different types of host cells and to persist chronically in the tissues of human and animal hosts. These qualities and the lack of an effective treatment for the chronic stage of the disease have contributed to the durability and the spread of the disease around the world. There is an urgent necessity to find new therapies for Chagas disease. Drug repurposing is a promising and cost-saving strategy for finding new drugs for different illnesses. In this work we describe the effect of carvedilol on T. cruzi. This compound, selected by virtual screening, increased the accumulation of immature autophagosomes characterized by lower acidity and hydrolytic properties. As a consequence of this action, the survival of trypomastigotes and the replication of epimastigotes and amastigotes were impaired, resulting in a significant reduction of infection and parasite load. Furthermore, carvedilol reduced the whole-body parasite burden peak in infected mice. In summary, in this work we present a repurposed drug with a significant in vitro and in vivo activity against T. cruzi. These data in addition to other pharmacological properties make carvedilol an attractive lead for Chagas disease treatment.

Tumor pyruvate kinase M2 modulators: a comprehensive account of activators and inhibitors as anticancer agents

Pyruvate kinase M2 (PKM2) catalyzes the conversion of phosphoenolpyruvate (PEP) to pyruvate. It plays a central role in the metabolic reprogramming of cancer cells and is expressed in most human tumors. It is essential in indiscriminate proliferation, survival, and tackling apoptosis in cancer cells. This positions PKM2 as a hot target in cancer therapy. Despite its well-known structure and several reported modulators targeting PKM2 as activators or inhibitors, a comprehensive review focusing on such modulators is lacking. Herein we summarize modulators of PKM2, the assays used to detect their potential, the preferable tense (T) and relaxed (R) states in which the enzyme resides, lacunae in existing modulators, and several strategies that may lead to effective anticancer drug development targeting PKM2.

Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of nsp13 helicase

The coronavirus disease 2019 (COVID-19) pandemic, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global public health challenge. While the efficacy of vaccines against emerging and future virus variants remains unclear, there is a need for therapeutics. Repurposing existing drugs represents a promising and potentially rapid opportunity to find novel antivirals against SARS-CoV-2. The virus encodes at least nine enzymatic activities that are potential drug targets. Here, we have expressed, purified and developed enzymatic assays for SARS-CoV-2 nsp13 helicase, a viral replication protein that is essential for the coronavirus life cycle. We screened a custom chemical library of over 5000 previously characterized pharmaceuticals for nsp13 inhibitors using a fluorescence resonance energy transfer-based high-throughput screening approach. From this, we have identified FPA-124 and several suramin-related compounds as novel inhibitors of nsp13 helicase activity in vitro. We describe the efficacy of these drugs using assays we developed to monitor SARS-CoV-2 growth in Vero E6 cells.

Structure-based in silico approaches for drug discovery against Mycobacterium tuberculosis

Mycobacterium tuberculosis is the causative agent of TB and was estimated to cause 1.4 million death in 2019, alongside 10 million new infections. Drug resistance is a growing issue, with multi-drug resistant infections representing 3.3% of all new infections, hence novel antimycobacterial drugs are urgently required to combat this growing health emergency. Alongside this, increased knowledge of gene essentiality in the pathogenic organism and larger compound databases can aid in the discovery of new drug compounds. The number of protein structures, X-ray based and modelled, is increasing and now accounts for greater than > 80% of all predicted M. tuberculosis proteins; allowing novel targets to be investigated. This review will focus on structure-based in silico approaches for drug discovery, covering a range of complexities and computational demands, with associated antimycobacterial examples. This includes molecular docking, molecular dynamic simulations, ensemble docking and free energy calculations. Applications of machine learning onto each of these approaches will be discussed. The need for experimental validation of computational hits is an essential component, which is unfortunately missing from many current studies. The future outlooks of these approaches will also be discussed.

(±)-: Pentatarget-Directed Ligand combining Cholinesterase, Monoamine Oxidase, and Glycogen Synthase Kinase 3β Inhibition with Calcium Channel Antagonism and Antiaggregating Properties for Alzheimer's Disease

Multitarget-directed ligands (MTDLs) are considered a promising therapeutic strategy to address the multifactorial nature of Alzheimer's disease (AD). Novel MTDLs have been designed as inhibitors of human acetylcholinesterases/butyrylcholinesterases, monoamine oxidase A/B, and glycogen synthase kinase 3β and as calcium channel antagonists via the Biginelli multicomponent reaction. Among these MTDLs, (±)-BIGI-3h was identified as a promising new hit compound showing in vitro balanced activities toward the aforementioned recognized AD targets. Additional in vitro studies demonstrated antioxidant effects and brain penetration, along with the ability to inhibit the aggregation of both τ protein and β-amyloid peptide. The in vivo studies have shown that (±)-BIGI-3h (10 mg/kg intraperitoneally) significantly reduces scopolamine-induced cognitive deficits.

Chemoinformatics Studies on a Series of Imidazoles as Cruzain Inhibitors

Natural products based on imidazole scaffolds have inspired the discovery of a wide variety of bioactive compounds. Herein, a series of imidazoles that act as competitive and potent cruzain inhibitors was investigated using a combination of ligand- and structure-based drug design strategies. Quantitative structure-activity relationships (QSARs) were generated along with the investigation of enzyme-inhibitor molecular interactions. Predictive hologram QSAR (HQSAR, r²_pred = 0.80) and AutoQSAR (q² = 0.90) models were built, and key structural properties that underpin cruzain inhibition were identified. Moreover, comparative molecular field analysis (CoMFA, r²_pred = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r²_pred = 0.73) revealed 3D molecular features that strongly affect the activity of the inhibitors. These findings were examined along with molecular docking studies and were highly compatible with the intermolecular contacts that take place between cruzain and the inhibitors. The results gathered herein revealed the main factors that determine the activity of the imidazoles studied and provide novel knowledge for the design of improved cruzain inhibitors.

Predictive Global Models of Cruzain Inhibitors with Large Chemical Coverage

Chagas disease affects 8-11 million people worldwide, most of them living in Latin America. Moreover, migratory phenomena have spread the infection beyond endemic areas. Efforts for the development of new pharmacological therapies are paramount as the pharmacological profile of the two marketed drugs currently available, nifurtimox and benznidazole, needs to be improved. Cruzain, a parasitic cysteine protease, is one of the most attractive biological targets due to its roles in parasite survival and immune evasion. In this work, we compiled and curated a database of diverse cruzain inhibitors previously reported in the literature. From this data set, quantitative structure-activity relationship (QSAR) models for the prediction of their pIC50 values were generated using k-nearest neighbors and random forest algorithms. Local and global models were calculated and compared. The statistical parameters for internal and external validation indicate a significant predictability, with q loo 2 values around 0.66 and 0.61 and external R 2 coefficients of 0.725 and 0.766. The applicability domain is quantitatively defined, according to QSAR good practices, using the leverage and similarity methods. The models described in this work are readily available in a Python script for the discovery of novel cruzain inhibitors.

Novel drug discovery platform for spinocerebellar ataxia, using fluorescence technology targeting β-III-spectrin

Numerous diseases are linked to mutations in the actin-binding domains (ABDs) of conserved cytoskeletal proteins, including β-III-spectrin, α-actinin, filamin, and dystrophin. A β-III-spectrin ABD mutation (L253P) linked to spinocerebellar ataxia type 5 (SCA5) causes a dramatic increase in actin binding. Reducing actin binding of L253P is thus a potential therapeutic approach for SCA5 pathogenesis. Here, we validate a high-throughput screening (HTS) assay to discover potential disrupters of the interaction between the mutant β-III-spectrin ABD and actin in live cells. This assay monitors FRET between fluorescent proteins fused to the mutant ABD and the actin-binding peptide Lifeact, in HEK293-6E cells. Using a specific and high-affinity actin-binding tool compound, swinholide A, we demonstrate HTS compatibility with an excellent Z'-factor of 0.67 ± 0.03. Screening a library of 1280 pharmacologically active compounds in 1536-well plates to determine assay robustness, we demonstrate high reproducibility across plates and across days. We identified nine Hits that reduced FRET between Lifeact and ABD. Four of those Hits were found to reduce Lifeact cosedimentation with actin, thus establishing the potential of our assay for detection of actin-binding modulators. Concurrent to our primary FRET assay, we also developed a high-throughput compatible counter screen to remove undesirable FRET Hits. Using the FRET Hits, we show that our counter screen is sensitive to undesirable compounds that cause cell toxicity or ABD aggregation. Overall, our FRET-based HTS platform sets the stage to screen large compound libraries for modulators of β-III-spectrin, or disease-linked spectrin-related proteins, for therapeutic development.

Application of In Silico and HTS Approaches to Identify Nuclear Import Inhibitors for Venezuelan Equine Encephalitis Virus Capsid Protein: A Case Study

The development of new drugs is costly and time-consuming, with estimates of over $US1 billion and 15 years for a product to reach the market. As understanding of the molecular basis of disease improves, various approaches have been used to target specific molecular interactions in the search for effective drugs. These include high-throughput screening (HTS) for novel drug identification and computer-aided drug design (CADD) to assess the properties of putative drugs before experimental work begins. We have applied conventional HTS and CADD approaches to the problem of identifying antiviral compounds to limit infection by Venezuelan equine encephalitis virus (VEEV). Nuclear targeting of the VEEV capsid (CP) protein through interaction with the host nuclear import machinery has been shown to be essential for viral pathogenicity, with viruses incapable of this interaction being greatly attenuated. Our previous conventional HTS and in silico structure-based drug design (SBDD) screens were successful in identifying novel inhibitors of CP interaction with the host nuclear import machinery, thus providing a unique opportunity to assess the relative value of the two screening approaches directly. This focused review compares and contrasts the two screening approaches, together with the properties of the inhibitors identified, as a case study for parallel use of the two approaches to identify antivirals. The utility of SBDD screens, especially when used in parallel with traditional HTS, in identifying agents of interest to target the host-pathogen interface is highlighted.

Exploring the Catalytic Reaction of Cysteine Proteases

Cysteine proteases play a major role in many life processes and are the target of key drugs. The reaction mechanism of these enzymes is a complex process, which involves several steps that are divided into two main groups: acylation and deacylation. In this work, we studied the energy profile for the acylation and a part of the deacylation reaction of three different enzymes, cruzain, papain, and the Q19A-mutated papain with the benzyloxycarbonyl-phenylalanylarginine-4-methylcoumaryl-7-amide (CBZ-FR-AMC) substrate. The calculations were performed using the EVB and PDLD/S-LRA methods. The overall agreement between the calculated and observed results is encouraging and indicates that we captured the correct reaction mechanism. Finally, our finding indicates that the minimum of the reaction profile, between the acylation and deacylation steps, should provide an excellent state for the binding of covalent inhibitors.

Crystal structure of Leishmania mexicana cysteine protease B in complex with a high-affinity azadipeptide nitrile inhibitor

Leishmania mexicana is an obligate intracellular protozoan parasite that causes the cutaneous form of leishmaniasis affecting South America and Mexico. The cysteine protease LmCPB is essential for the virulence of the parasite and therefore, it is an appealing target for antiparasitic therapy. A library of nitrile-based cysteine protease inhibitors was screened against LmCPB to develop a treatment of cutaneous leishmaniasis. Several compounds are sufficiently high-affinity LmCPB inhibitors to serve both as starting points for drug discovery projects and as probes for target validation. A 1.4 Å X ray crystal structure, the first to be reported for LmCPB, was determined for the complex of this enzyme covalently bound to an azadipeptide nitrile ligand. Mapping the structure-activity relationships for LmCPB inhibition revealed superadditive effects for two pairs of structural transformations. Therefore, this work advances our understanding of azadipeptidyl and dipeptidyl nitrile structure-activity relationships for LmCPB structure-based inhibitor design. We also tested the same series of inhibitors on related cysteine proteases cathepsin L and Trypanosoma cruzi cruzain. The modulation of these mammalian and protozoan proteases represents a new framework for targeting papain-like cysteine proteases.

Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction

Natural products comprise a rich reservoir for innovative drug leads and are a constant source of bioactive compounds. To find pharmacological targets for new or already known natural products using modern computer-aided methods is a current endeavor in drug discovery. Nature's treasures, however, could be used more effectively. Yet, reliable pipelines for the large-scale target prediction of natural products are still rare. We developed an in silico workflow consisting of four independent, stand-alone target prediction tools and evaluated its performance on dihydrochalcones (DHCs)-a well-known class of natural products. Thereby, we revealed four previously unreported protein targets for DHCs, namely 5-lipoxygenase, cyclooxygenase-1, 17β-hydroxysteroid dehydrogenase 3, and aldo-keto reductase 1C3. Moreover, we provide a thorough strategy on how to perform computational target predictions and guidance on using the respective tools.

Gallotannins are non-specific inhibitors of α-amylase: Aggregates are the active species taking part in inhibition

The versatile biological activity of gallotannins has been investigated for a long time, including their use as α-amylase inhibitors for the treatment of diabetes and its complications. The effectiveness of gallotannins on a wide range of enzymes refers to promiscuity. We proved that gallotannins are non-specific promiscuous α-amylase inhibitors, which exert their effect through their aggregates. A gallotannin of Aleppo oak origin fulfilled all the criteria for aggregators; significant changes could be observed in the IC₅₀ values in the presence of Triton^™ X-100 detergent (from 2.3 to 110 μg/ml) and after enzyme-inhibitor preincubation (from 2.3 to 0.65 μg/ml). Increasing the enzyme concentration also led to the moderation of the inhibition by gallotannin. In addition, we observed that gallotannin molecules are those, which are involved in aggregation, and discrete protein molecules are adsorbed to the aggregates. This was revealed by the increasing particle size of gallotannin, which became three orders of magnitude higher after 150 min, whereas the size of α-amylase remained unchanged. Consequently, gallotannins should be used as anti-diabetic drugs only if the necessity of higher dose due to their promiscuity is taken into account. Aggregation propensity should not be ignored in case of in vivo applications.

The role of imidazole and benzimidazole heterocycles in Chagas disease: A review

The haemoflagellate protozoan Trypanosoma cruzi (T. cruzi) is the causative agent of Chagas disease (CD), a potentially life-threatening disease. Little by little, remarkable progress has been achieved against CD, although it is still not enough. In the absence of effective chemotherapy, many research groups, organizations and pharmaceutical companies have focused their efforts on the search for compounds that could become viable drugs against CD. Within the wide variety of reported derivatives, this review summarizes and provides a global vision of the situation of those compounds that include broadly studied heterocycles in their structures due to their applications in medicinal chemistry: imidazole and benzimidazole rings. Therefore, the intention of this work is to present a compilation, as much as possible, of all the reported information, regarding these imidazole and benzimidazole derivatives against T. cruzi, as a starting point for future researchers in this field.