Antioxidant capacity of simplified oxygen heterocycles and proposed derivatives by theoretical calculations.

CONTEXT: Some structural properties can be involved in the antioxidant capacity of several polyphenol derivatives, among them their simplified structures. This study examines the contribution of simplified structure for the antioxidant capacity of some natural and synthetic antioxidants. The resonance structures were related to the π-type electron system of carbon-carbon double bonds between both phenyl rings. Trans-resveratrol, phenyl-benzofuran, phenyl-indenone, and benzylidene-benzofuranone are the best basic antioxidant templates among the simplified derivatives studied here. Additionally, the stilbene moiety was found on the molecules with the best antioxidant capacity. Furthermore, our investigation suggests that these compounds can be used as antioxidant scaffold for designing and developing of new promising derivatives. METHODS: To investigate the structure-antioxidant capacity for sixteen simplified natural and proposed derivatives we have employed density functional theory and used Gaussian 09. Our DFT calculations were performed using the B3LYP functional and the 6-31+G(d,p) basis set. All electron transfer mechanisms were investigated by using values of HOMO, ionization potential, energy affinity, stabilization energies, and spin density distributions.

A PLS study on the psychotropic activity for a series of cannabinoid compounds.

INTRODUCTION: The use of the Cannabis sativa plant by man has been common for centuries due to its numerous therapeutic properties resulting from the compounds present in it, called cannabinoids. However, the use of these compounds as drugs is still limited due to the psychotropic effects caused by them. The proteins that act as receptors of cannabinoid compounds were identified and characterized, being called CB1 and CB2 receptors. There is a series of 50 cannabinoid compounds that was studied through quantum and chemometric methods in order to obtain a mathematical model that could relate the structure of these compounds to their psychotropic activity. That model proved to be effective by predicting the psychoactivity of the 50 compounds from the series and elucidating relevant characteristics that imply in psychoactivity. However, most of these 50 compounds do not have experimental data of biological activity with CB1 and CB2 receptors. OBJECTIVES: This study aims to generate QSAR models in order to predict the biological activity of the 50 cannabinoid compounds and then relate the predicted biological activity values to the already known psychoactivity. METHODS: Another series of cannabinoid compounds was selected to generate and validate QSAR models, aiming to predict the biological activity of the 50 cannabinoid compounds with both CB1 and CB2 receptors. RESULTS: The PLS-CB1 and PLS-CB2 QSAR models were generated and validated in this work, proving to be highly predictive, and the biological activities (pK ) of the 50 cannabinoid compounds were predicted by them. It is important to highlight compounds Ic14, Ic18, and Ic19 (psychotropic inactive) which presented higher predicted pK values than the main cannabinoid compounds (Δ9-THC and Δ8-THC). Also, compound Ic21 stood out as the highest value of the predicted biological activities in the interaction with the CB2 receptor. CONCLUSION: The generated PLS models and the predicted pKi values of the 50 cannabinoid compounds can provide valuable information in the drug design of new cannabinoid compounds that can interact with CB1 and CB2 receptors in a therapeutic way with no psychotropic effects.

Towards a relationship between photoluminescence emissions and photocatalytic activity of Ag2SeO4: combining experimental data and theoretical insights.

A systematic theoretical and experimental study was carried out to find a relationship between photoluminescence emissions and photocatalytic activity of Ag2SeO4 obtained by different synthesis methods (sonochemistry, ultrasonic probe, coprecipitation and microwave assisted hydrothermal synthesis). Experimental characterization techniques (XRD with Rietveld refinement, Raman, FTIR, UV-vis, XPS and photoluminescence spectroscopy) were used to elucidate its structural order at short, medium, and long ranges. Morphological analysis performed by FE-SEM showed distinct morphologies due to the different methods of synthesis. Based on density functional theory (DFT) calculations, it was possible to study in detail the Ag2SeO4 surface properties, including its surface energy, geometry, and electronic structure for the (100), (010), (001), (101), (011), (110), (111), (021), (012) and (121) surfaces. The equilibrium morphology of Ag2SeO4 was predicted as a truncated octahedron with exposed (111), (001), (010) and (011) surfaces. Photoluminescence emissions showed a band covering the visible spectrum, and the Ag2SeO4 obtained by the coprecipitation method presented the most intense band with a maximum in the red region. Photocatalytic results confirmed that Ag2SeO4 synthesized by the sonochemistry method is the best photocatalyst for rhodamine B degradation under UV light irradiation.

Examining the Effect of Charged Lipids on Mitochondrial Outer Membrane Dynamics Using Atomistic Simulations.

The outer mitochondrial membrane (OMM) is involved in multiple cellular functions such as apoptosis, inflammation and signaling via its membrane-associated and -embedded proteins. Despite the central role of the OMM in these vital phenomena, the structure and dynamics of the membrane have regularly been investigated in silico using simple two-component models. Accordingly, the aim was to generate the realistic multi-component model of the OMM and inspect its properties using atomistic molecular dynamics (MD) simulations. All major lipid components, phosphatidylinositol (PI), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylserine (PS), were included in the probed OMM models. Because increased levels of anionic PS lipids have potential effects on schizophrenia and, more specifically, on monoamine oxidase B enzyme activity, the effect of varying the PS concentration was explored. The MD simulations indicate that the complex membrane lipid composition (MLC) behavior is notably different from the two-component PC-PE model. The MLC changes caused relatively minor effects on the membrane structural properties such as membrane thickness or area per lipid; however, notable effects could be seen with the dynamical parameters at the water-membrane interface. Increase of PS levels appears to slow down lateral diffusion of all lipids and, in general, the presence of anionic lipids reduced hydration and slowed down the PE headgroup rotation. In addition, sodium ions could neutralize the membrane surface, when PI was the main anionic component; however, a similar effect was not seen for high PS levels. Based on these results, it is advisable for future studies on the OMM and its protein or ligand partners, especially when wanting to replicate the correct properties on the water-membrane interface, to use models that are sufficiently complex, containing anionic lipid types, PI in particular.

A partial least squares and artificial neural network study for a series of arylpiperazines as antidepressant agents.

Depression affects more than 300 million people around the world and can lead to suicide. About 30% of patients on treatment for depression drop out of therapy due to side effects or to latency time associated to therapeutic effects. 5-HT receptor, known as serotonin, is considered the key in depression treatment. Arylpiperazine compounds are responsible for several pharmacological effects and are considered as ligands in serotonin receptors, such as the subtype 5-HT2a. Here, in silico studies were developed using partial least squares (PLSs) and artificial neural networks (ANNs) to design new arylpiperazine compounds that could interact with the 5-HT2a receptor. First, molecular and electronic descriptors were calculated and posteriorly selected from correlation matrixes and genetic algorithm (GA). Then, the selected descriptors were used to construct PLS and ANN models that showed to be robust and predictive. Lastly, new arylpiperazine compounds were designed and their biological activity values were predicted by both PLS and ANN models. It is worth to highlight compounds G5 and G7 (predicted by the PLS model) and G3 and G15 (predicted by the ANN model), whose predicted pIC50 values were as high as the three highest values from the arylpiperazine original set studied here. Therefore, it can be asserted that the two models (PLS and ANN) proposed in this work are promising for the prediction of the biological activity of new arylpiperazine compounds and may significantly contribute to the design of new drugs for the treatment of depression.

Drug design of new 5-HT6R antagonists aided by artificial neural networks.

Alzheimer's Disease (AD) is the most frequent illness and cause of death amongst the age related-neurodegenerative disorders. The Alzheimer's Disease International (ADI) reported in 2019 that over 50 million people were living with dementia in the world and this number could potentially be around 152 million by 2050.5-hydroxtryptamine subtype 6 receptor (5-HT6R) has been identified as a potential anti-amnesic drug target and therefore, the administration of 5-HT6R antagonists can likely mitigate the memory loss and intellectual deterioration associated with AD. Herein, computational tools were applied to design new 5-HT6 antagonists and their biological activity values were predicted by our QSAR model obtained from Artificial Neural Networks (ANN). The proposed compounds here from the QSAR-ANN model presented significant biological activity values and some of them have achieved pKi above 9.00. Furthermore, our results suggest that the presence of halogen atoms (especially bromine) linked to the aromatic ring at para-position (HYD) contribute considerably to the increase of the biological activity values while bulky groups in the PI position do not culminate with the increase antagonist activity of compounds here analyzed. Finally, the ADME/Tox profile as well as the synthetic accessibility of new proposed compounds qualify them to go on further with experimental procedures and thenceforward their antagonist effects can be confirmed.

Experimental and theoretical study on structure-tautomerism among edaravone, isoxazolone, and their heterocycles derivatives as antioxidants.

Edaravone is a heterocyclic pyrazolone compound. It has pronounced effect against free radicals, however renal and hepatic disorders have been reported. Isoxazolones are considered bioisosteric analogues of pyrazolones and may have comparable properties. Thus, we investigated the structural and electronic influences for edaravone, isoxazolone, and their tautomers on antioxidant process. Structure and tautomerism study among edaravone, isoxazolone and their heterocycles derivatives were related to antioxidant mechanisms by using the hybrid DFT method B3LYP with the basis sets 6-31++G(2d,2p). The C-H tautomer was the most stable and energetically favored among them. Intramolecular N-H-N hydrogen bonds and polar medium were responsible for the low energy differences among all possible tautomers. N-H tautomers in both systems proved to be better antioxidant by SET (single electron transfer), while O-H tautomers were better antioxidant on HAT (homolytic hydrogen atom transfer) mechanism. Theoretical calculation showed that edaravone is more potent than phenylisoxazolone, however, both has similar antioxidant scavenging on experimental DPPH. The carbonyliminic system played a very important role in the antioxidant activity for both studied classes.

Microwave-Driven Hexagonal-to-Monoclinic Transition in BiPO4: An In-Depth Experimental Investigation and First-Principles Study.

Present theoretical and experimental work provides an in-depth understanding of the morphological, structural, electronic, and optical properties of hexagonal and monoclinic polymorphs of bismuth phosphate (BiPO4). Herein, we demonstrate how microwave irradiation induces the transformation of a hexagonal phase to a monoclinic phase in a short period of time and, thus, the photocatalytic performance of BiPO4. To complement and rationalize the experimental results, first-principles calculations have been performed within the framework of density functional theory. This was aimed at obtaining the geometric, energetic, and structural parameters as well as vibrational frequencies; further, the electronic properties (band structure diagram and density of states) of the bulk and corresponding surfaces of both the hexagonal and monoclinic phases of BiPO4 were also acquired. A detailed characterization of the low vibrational modes of both the hexagonal and monoclinic polymorphs is key to explaining the irreversible phase transformation from hexagonal to monoclinic. On the basis of the calculated values of the surface energies, a map of the available morphologies of both phases was obtained by using Wulff construction and compared to the observed scanning electron microscopy images. The BiPO4 crystals obtained after 16-32 min of microwave irradiation provided excellent photodegradation of Rhodamine B under visible-light irradiation. This enhancement was found to be related to the surface energy and the types of clusters formed on the exposed surfaces of the morphology. These findings provide details of the hexagonal-to-monoclinic phase transition in BiPO4 during microwave irradiation; further, the results will assist in the design of electronic devices with higher efficiency and reliability.

A Proposal for the Mechanism of the CH + CO2 Reaction.

Few experimental studies on the CH + CO2 global reaction propose H, CO, and HCO as major products. However, the reaction mechanisms behind this process have not yet been elucidated. Moreover, some intriguing kinetic particularities were noticed in these previous investigations. The advanced theoretical study performed here shows that a CH insertion mechanism is capable of explaining all the experimental data available. Hence, the strong deviations from a traditional Arrhenius behavior ascribed to the rate-determining elementary reaction (the CH insertion step) account for the kinetic particularities observed experimentally. A change in the preferred product channel as temperatures increase (from HCO + CO to H + 2CO) is also predicted to occur due to the HCO decomposition, although the CH depletion rates in typical conditions are not affected by this additional step.

Advances and Perspectives in Applying Deep Learning for Drug Design and Discovery.

Discovering (or planning) a new drug candidate involves many parameters, which makes this process slow, costly, and leading to failures at the end in some cases. In the last decades, we have witnessed a revolution in the computational area (hardware, software, large-scale computing, etc.), as well as an explosion in data generation (big data), which raises the need for more sophisticated algorithms to analyze this myriad of data. In this scenario, we can highlight the potentialities of artificial intelligence (AI) or computational intelligence (CI) as a powerful tool to analyze medicinal chemistry data. According to IEEE, computational intelligence involves the theory, the design, the application, and the development of biologically and linguistically motivated computational paradigms. In addition, CI encompasses three main methodologies: neural networks (NN), fuzzy systems, and evolutionary computation. In particular, artificial neural networks have been successfully applied in medicinal chemistry studies. A branch of the NN area that has attracted a lot of attention refers to deep learning (DL) due to its generalization power and ability to extract features from data. Therefore, in this mini-review we will briefly outline the present scope, advances, and challenges related to the use of DL in drug design and discovery, describing successful studies involving quantitative structure-activity relationships (QSAR) and virtual screening (VS) of databases containing thousands of compounds.

New consensus multivariate models based on PLS and ANN studies of sigma-1 receptor antagonists.

The treatment of neuropathic pain is very complex and there are few drugs approved for this purpose. Among the studied compounds in the literature, sigma-1 receptor antagonists have shown to be promising. In order to develop QSAR studies applied to the compounds of 1-arylpyrazole derivatives, multivariate analyses have been performed in this work using partial least square (PLS) and artificial neural network (ANN) methods. A PLS model has been obtained and validated with 45 compounds in the training set and 13 compounds in the test set (r2training = 0.761, q2 = 0.656, r2test = 0.746, MSEtest = 0.132 and MAEtest = 0.258). Additionally, multi-layer perceptron ANNs (MLP-ANNs) were employed in order to propose non-linear models trained by gradient descent with momentum backpropagation function. Based on MSEtest values, the best MLP-ANN models were combined in a MLP-ANN consensus model (MLP-ANN-CM; r2test = 0.824, MSEtest = 0.088 and MAEtest = 0.197). In the end, a general consensus model (GCM) has been obtained using PLS and MLP-ANN-CM models (r2test = 0.811, MSEtest = 0.100 and MAEtest = 0.218). Besides, the selected descriptors (GGI6, Mor23m, SRW06, H7m, MLOGP, and µ) revealed important features that should be considered when one is planning new compounds of the 1-arylpyrazole class. The multivariate models proposed in this work are definitely a powerful tool for the rational drug design of new compounds for neuropathic pain treatment. Graphical abstract Main scaffold of the 1-arylpyrazole derivatives and the selected descriptors.

Intramolecular interactions, isomerization and vibrational frequencies of two paracetamol analogues: A spectroscopic and a computational approach.

The aim of this investigation was to determine the molecular properties and provide an interpretation of the vibrational mode couplings of these two paracetamol analogues: 2-bromo-2-methyl-N-(4-nitrophenyl)-propanamide and 2-bromo-2-methyl-N-p-tolyl-propanamide. E/Z isomers, keto/enol unimolecular rearrangement and prediction of the transition state structures in each mechanism were also assessed using the Density Functional Theory (DFT). The DFT estimates a high energy gap between E and Z isomers (9-11 kcal·mol(-1)), with barrier heights ranging from 16 to 19 kcal·mol(-1). In contrast, the barrier energies on the keto/enol isomerization are almost 10 kcal·mol(-1) higher than those estimated for the E/Z rearrangement. The kinetic rate constant was also determined for each reaction mechanism. Natural bond orbital analysis and the quantum theory of atoms in molecules were used to interpret the intramolecular hydrogen bonds and to understand the most important interactions that govern the stabilization of each isomer. Furthermore, an analysis of the atomic charge distribution using different population methodologies was also performed.

Accurate Gaussian basis sets for atomic and molecular calculations obtained from the generator coordinate method with polynomial discretization.

Accurate Gaussian basis sets for atoms from H to Ba were obtained by means of the generator coordinate Hartree-Fock (GCHF) method based on a polynomial expansion to discretize the Griffin-Wheeler-Hartree-Fock equations (GWHF). The discretization of the GWHF equations in this procedure is based on a mesh of points not equally distributed in contrast with the original GCHF method. The results of atomic Hartree-Fock energies demonstrate the capability of these polynomial expansions in designing compact and accurate basis sets to be used in molecular calculations and the maximum error found when compared to numerical values is only 0.788 mHartree for indium. Some test calculations with the B3LYP exchange-correlation functional for N2, F2, CO, NO, HF, and HCN show that total energies within 1.0 to 2.4 mHartree compared to the cc-pV5Z basis sets are attained with our contracted bases with a much smaller number of polarization functions (2p1d and 2d1f for hydrogen and heavier atoms, respectively). Other molecular calculations performed here are also in very good accordance with experimental and cc-pV5Z results. The most important point to be mentioned here is that our generator coordinate basis sets required only a tiny fraction of the computational time when compared to B3LYP/cc-pV5Z calculations.

Understanding the cytotoxicity or cytoprotective effects of biological and synthetic quinone derivatives by redox mechanism.

Quinones represent an important class of biological compounds, but are also involved with toxicological intermediates and among their hazardous effects include cytotoxicity, immunotoxicity, and carcinogenesis. The structure-toxicity relationship for quinone derivatives has been used to cytotoxicity or cytoprotective effects by redox mechanism is determined using quantum chemical calculations through the density functional theory (DFT). According to our DFT study, the electron acceptance is related with LUMO, electron affinity, and stabilization energy values. The highest spin density distribution in the heteroatoms is more favored for the more cytotoxic compounds. The electrophilic capacities of these compounds have been related with LUMO values. The cytotoxic properties of quinones are related to the stabilization energy after electron accepting by redox mechanism. Electron affinity is the most relevant parameter related to toxicity mechanism. Regioisomers has different electrophilic capacity. The electrophilicity increases on molecules containing electron-withdrawing groups (EWG) and reduces on molecules containing electron-donating groups (EDG). These results explain the toxic difference between natural and synthetic quinone derivatives and can be used in the design and study of new drugs.

The CH3PH2 and CH3PH isomers: isomerization, hydrogen release, thermodynamic, and spectroscopy properties.

In this study was performed a quantum chemical investigation of the methylphosphine molecule and its radical, which may show potential implications in interstellar processes, and may be crucial atmospheric tracer gasses in the atmosphere of Giant planets. The analyses were performed with the density functional theory and coupled cluster methods. The anharmonic vibrational modes were predicted for all the isomers. The atomic charge distribution was analyzed with different methodologies and some methods fail to establish the correct sign for phosphorous atom charges. The CH2PH2/CH3PH and CHPH3/CH3PH energy gap is 16.45-17.43 and 67.05-69.02 kcal mol(-1), respectively. The CH2PH3/CH3PH2 energy difference ranges from 44.62 to 50.05 kcal mol(-1). The ionization energy predicted with the W1BD method for CH3PH and CH3PH2 are 8.73 and 9.01 eV, respectively. The heat of formation at 298 K for each molecule were calculated in kcal mol(-1): CH3PH (24.16-25.27), CH2PH2 (41.20-42.47), CHPH3 (92.50-94.23), CH3PH2 (-4.73-2.83) and CH2PH3 (40.03-42.55). The rotational energy barriers for CH3PH2 and CH2PH3 are 1.65 and 2.81 kcal mol(-1), respectively. The CHPH3→CH2PH2 unimolecular arrangement presents a barrier energy of 29.89 kcal mol(-1), whereas CH3PH→CH2PH2 is accessible overcoming a barrier of 42.42 kcal mol(-1). The H2-release routes for CH2PH2 from carbon and phosphorous atoms show a barrier of 98.19 and 46.67 kcal mol(-1), respectively. For the CH3PH2→CH2PH3 isomerization, an energy barrier of 94.00 kcal mol(-1) was predicted, while for the H2-release pathway for CH3PH2 it is necessary to pass a potential energy barrier of 97.56 kcal mol(-1).

Pattern recognition techniques applied to the study of leishmanial glyceraldehyde-3-phosphate dehydrogenase inhibition.

Chemometric pattern recognition techniques were employed in order to obtain Structure-Activity Relationship (SAR) models relating the structures of a series of adenosine compounds to the affinity for glyceraldehyde 3-phosphate dehydrogenase of Leishmania mexicana (LmGAPDH). A training set of 49 compounds was used to build the models and the best ones were obtained with one geometrical and four electronic descriptors. Classification models were externally validated by predictions for a test set of 14 compounds not used in the model building process. Results of good quality were obtained, as verified by the correct classifications achieved. Moreover, the results are in good agreement with previous SAR studies on these molecules, to such an extent that we can suggest that these findings may help in further investigations on ligands of LmGAPDH capable of improving treatment of leishmaniasis.

Molecular properties of the PCO radical: heat of formation and the isomerization pathways.

The potential energy surface of [P,C,O] system in the ground state was investigated by quantum chemical methods. Four different isomers were characterized at the B3LYP/aug-cc-pVTZ: COP (i1), cPCO (i2), PCO (i3), and CPO (i4). The linear species i3 is the global minimum in the ground state surface, while i4 is a bent structure, and i2 is a cyclic isomer. In view to evaluate the bond nature of each isomer, a QTAIM and a NBO analyses were applied. The triangular species presents a ring critical point which confirms its cyclic structure instead of a T-shape one. The stability increases in the following order: i3 > i2 > i1 > i4. The energy gap between i3 and i2 ranges from 49.20 to 51.15 kcal mol(-1). The reaction barrier energies that converge into the direction of i3 showed values around 10 kcal mol(-1), while the reverse barriers are considerably large (62.85 kcal mol(-1)). The i3 heat of formation at 298 K ranges from 11.83 to 19.41 kcal mol(-1).

Molecular features related to HIV integrase inhibition obtained from structure- and ligand-based approaches.

Among several biological targets to treat AIDS, HIV integrase is a promising enzyme that can be employed to develop new anti-HIV agents. The aim of this work is to propose a mechanistic interpretation of HIV-1 integrase inhibition and to rationalize the molecular features related to the binding affinity of studied ligands. A set of 79 HIV-1 integrase inhibitors and its relationship with biological activity are investigated employing 2D and 3D QSAR models, docking analysis and DFT studies. Analyses of docking poses and frontier molecular orbitals revealed important features on the main ligand-receptor interactions. 2D and 3D models presenting good internal consistency, predictive power and stability were obtained in all cases. Significant correlation coefficients (r(2) = 0.908 and q(2)= 0.643 for 2D model; r(2)= 0.904 and q(2)= 0.719 for 3D model) were obtained, indicating the potential of these models for untested compounds. The generated holograms and contribution maps revealed important molecular requirements to HIV-1 IN inhibition and several evidences for molecular modifications. The final models along with information resulting from molecular orbitals, 2D contribution and 3D contour maps should be useful in the design of new inhibitors with increased potency and selectivity within the chemical diversity of the data.

Understanding the molecular aspects of tetrahydrocannabinol and cannabidiol as antioxidants.

An antioxidant mechanism of tetrahydrocannabinol (THC) and cannabidiol (CBD) were compared with a simplified model of α-tocopherol, butylhydroxytoluene and hydroxytoluene in order to understand the antioxidant nature of THC and CBD molecules using DFT. The following electronic properties were evaluated: frontier orbitals nature, ionization potential, O-H bond dissociation energy (BDEOH), stabilization energy, and spin density distribution. An important factor that shows an influence in the antioxidant property of THC is the electron abstraction at the phenol position. Our data indicate that the decrease of the HOMO values and the highest ionization potential values are related to phenol, ether, and alkyl moieties. On the other hand, BDEOH in molecules with the cyclohexenyl group at ortho position of phenol are formed from lower energies than the molecules with an ether group at the meta position. In the light of our results, the properties calculated here predict that THC has a sightly higher antioxidant potential than CBD.

Non-peptidic cruzain inhibitors with trypanocidal activity discovered by virtual screening and in vitro assay.

A multi-step cascade strategy using integrated ligand- and target-based virtual screening methods was developed to select a small number of compounds from the ZINC database to be evaluated for trypanocidal activity. Winnowing the database to 23 selected compounds, 12 non-covalent binding cruzain inhibitors with affinity values (K i) in the low micromolar range (3-60 µM) acting through a competitive inhibition mechanism were identified. This mechanism has been confirmed by determining the binding mode of the cruzain inhibitor Nequimed176 through X-ray crystallographic studies. Cruzain, a validated therapeutic target for new chemotherapy for Chagas disease, also shares high similarity with the mammalian homolog cathepsin L. Because increased activity of cathepsin L is related to invasive properties and has been linked to metastatic cancer cells, cruzain inhibitors from the same library were assayed against it. Affinity values were in a similar range (4-80 µM), yielding poor selectivity towards cruzain but raising the possibility of investigating such inhibitors for their effect on cell proliferation. In order to select the most promising enzyme inhibitors retaining trypanocidal activity for structure-activity relationship (SAR) studies, the most potent cruzain inhibitors were assayed against T. cruzi-infected cells. Two compounds were found to have trypanocidal activity. Using compound Nequimed42 as precursor, an SAR was established in which the 2-acetamidothiophene-3-carboxamide group was identified as essential for enzyme and parasite inhibition activities. The IC50 value for compound Nequimed42 acting against the trypomastigote form of the Tulahuen lacZ strain was found to be 10.6±0.1 µM, tenfold lower than that obtained for benznidazole, which was taken as positive control. In addition, by employing the strategy of molecular simplification, a smaller compound derived from Nequimed42 with a ligand efficiency (LE) of 0.33 kcal mol(-1) atom(-1) (compound Nequimed176) is highlighted as a novel non-peptidic, non-covalent cruzain inhibitor as a trypanocidal agent candidate for optimization.