Vinícius G. Maltarollo

Use of machine learning approaches for novel drug discovery

abstract Introduction: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds. Areas covered: This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening. Expert opinion: Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

Advanced QSAR Studies on PPARd Ligands Related to Metabolic Diseases

PPARd e um receptor nuclear que, quando ativado, regula o metabolismo de carboidratos e lipidios, e esta relacionado com diversas enfermidades, tais como sindrome metabolica e diabetes tipo 2. Para entender as principais interacoes entre alguns ligantes bioativos e o receptor PPARd, modelos de QSAR 2D e 3D foram obtidos e comparados com mapas de potencial eletrostatico (MEP) e dos orbitais de fronteira (HOMO e LUMO), assim como resultados de docagem molecular. Os modelos de QSAR obtidos apresentaram bons resultados estatisticos e foram utilizados para predizer a atividade biologica de compostos do conjunto-teste (validacao externa), e os valores preditos estao em concordância com os resultados experimentais. Alem disso, todos mapas moleculares foram utilizados para avaliar as possiveis interacoes entre os ligantes e o receptor PPARd. Portanto, os modelos de QSAR 2D e 3D, assim como os mapas de HOMO, LUMO e MEP, podem fornecer informacoes sobre as principais propriedades necessarias para o planejamento de novos ligantes do receptor PPARd. PPARd is a nuclear receptor that, when activated, regulates the metabolism of carbohydrates and lipids and is related to metabolic syndrome and type 2 diabetes. To understand the main interactions between ligands and PPARd, we have constructed 2D and 3D QSAR models and compared them with HOMO, LUMO and electrostatic potential maps of the compounds studied, as well as docking results. All QSAR models showed good statistical parameters and prediction outcomes. The QSAR models were used to predict the biological activity of an external test set, and the predicted values are in good agreement with the experimental results. Furthermore, we employed all maps to evaluate the possible interactions between the ligands and PPARd. These predictive QSAR models, along with the HOMO, LUMO and MEP maps, can provide insights into the structural and chemical properties that are needed in the design of new PPARd ligands that have improved biological activity and can be employed to treat metabolic diseases.

Computational studies of TGF-βRI (ALK-5) inhibitors: analysis of the binding interactions between ligand-receptor using 2D and 3D techniques.

ALK-5 (Activin-Like Kinase 5) is a biological receptor involved in a variety of pathological processes such as cancer and fibrosis. ALK-5 receptor propagates an intracellular signaling that forms a protein complex capable of reaching the nucleus and modulating the gene transcription. In the present study, comparative molecular field analysis (CoMFA) and hologram quantitative structure-activity relationship (HQSAR) studies were conducted on a series of potent ALK-5 inhibitors. Significant correlation coefficients (CoMFA, r(2)=0.99 and q(2)=0.85; HQSAR, r(2)=0.92 and q(2)=0.72) were obtained, indicating the predictive potential of the 2D and 3D models for untested compounds. The models were then used to predict the potency of a test set, and the predicted values from the HQSAR and CoMFA models were in good agreement with the experimental results. The final QSAR models, along with the information obtained from 3D (steric and electrostatic) contour maps and 2D contribution maps, can be useful for the design of novel bioactive ligands.

Structure-Based Virtual Screening and Discovery of New PPARδ/γ Dual Agonist and PPARδ and γ Agonists

Peroxisome proliferator-activated receptors (PPARs) are involved in the control of carbohydrate and lipid metabolism and are considered important targets to treat diabetes mellitus and metabolic syndrome. The available PPAR ligands have several side effects leading to health risks justifying the search for new bioactive ligands to activate the PPAR subtypes, in special PPARδ, the less studied PPAR isoform. Here, we used a structure-based virtual screening protocol in order to find out new PPAR ligands. From a lead-like subset of purchasable compounds, we identified 5 compounds with potential PPAR affinity and, from preliminary in vitro assays, 4 of them showed promising biological activity. Therefore, from our in silico and in vitro protocols, new PPAR ligands are potential candidates to treat metabolic diseases.

Benchmark studies of UV-vis spectra simulation for cinnamates with UV filter profile.

Skin cancer is a serious public health problem worldwide, being incident over all five continents and affecting an increasing number of people. As sunscreens are considered an important preventive measure, studies to develop better and safer sunscreens are crucial. Cinnamates are UVB filters with good efficiency and cost-benefit, therefore, their study could lead to the development of new UV filters. A benchmark to define the most suitable density functional theory (DFT) functional to predict UV–vis spectra for ethylhexyl methoxycinnamate was performed. Time-dependent DFT (TD-DFT) calculations were then carried out [B3LYP/6-311u2009+u2009G(d,p) and B3P86/6-311u2009+u2009G(d,p) in methanol environment] for seven cinammete derivatives implemented in the Gaussian 03 package. All DFT/TD-DFT simulations were performed after a conformational search with the Monte-Carlo method and MMFF94 force field. B3LYP and B3P86 functionals were better at reproducing closely the experimental spectra of ethylhexyl methoxycinnamate. Calculations of seven cinnamates showed a λmax of around 310xa0nm, corroborating literature reports. It was observed that the energy for the main electronic transition was around 3.95xa0eV and could be explained by electron delocalization on the aromatic ring and ester group, which is important to UV absorption. The methodology employed proved to be suitable for determination of the UV spectra of cinnamates and could be used as a tool for the development of novel UV filters.

Theoretical study of tautomers and photoisomers of avobenzone by DFT methods

AbstractOrganic ultraviolet (UV) filters such as cinnamates, benzophenones, p-aminobenzoic derivatives, and avobenzone (which have well-established and recognized UV-filtering efficacies) are employed in cosmetic/pharmaceutical products to minimize the harm caused by exposure of the skin to sunlight. In this study, a detailed investigation of the photostability and tautomerism mechanisms of avobenzone was performed utilizing DFT methods. The UV spectral profile of avobenzone was also simulated, and the results showed good agreement with experimental data. Furthermore, the calculations were able to distinguish tautomers and photoisomers of the studied organic filter based on their properties, thus showing the potential to develop new organic UV filters.n Graphical AbstractTheoretical studies of avobenzone and its tautomers by TD-DFT.

Convergent QSAR studies on a series of NK3 receptor antagonists for schizophrenia treatment

Abstract The dopamine hypothesis states that decreased dopaminergic neurotransmission reduces schizophrenia symptoms. Neurokinin-3 receptor (NK3) antagonists reduce dopamine release and have shown positive effects in pre-clinical and clinical trials. We employed 2D and 3D-QSAR analysis on a series of 40 non-peptide NK3 antagonists. Multivariate statistical analysis, PCA and HCA, were performed to rational training/test set splitting and PLS regression was employed to construct all QSAR models. We constructed one highly predictive CoMFA model (q2u2009=u20090.810 and r2u2009=u20090.929) and acceptable HQSAR and CoMSIA models (HQSAR q2u2009=u20090.644 and r2u2009=u20090.910; CoMSIA q2u2009=u20090.691, r2u2009=u20090.911). The three different techniques provided convergent physicochemical results. All models indicate cyclopropane, piperidine and di-chloro-phenyl ring attached to cyclopropane ring and also the amide group attached to the piperidine ring could play an important role in ligand–receptor interactions. These findings may contribute to develop potential NK3 receptor antagonists for schizophrenia.

Application of bioisosterism in design of the semicarbazone derivatives as cruzain inhibitors: a theoretical and experimental study

A series of semicarbazone, thiosemicarbazone, and aminoguanidine derivatives were synthesized and tested as antitrypanosomal agents. The theoretical NMR of the compounds was calculated using molecular modeling techniques (density functional theory (DFT) calculations) and confirmed the formation of the compounds. The ability to inhibit cruzain and Trypanosoma cruzi epimastigote replication was evaluated. Cruzain inhibition ranged between 70 and 75% (100 μM), and IC50 values observed in epimastigote forms of T. cruzi ranged from 20 to 140 μM. Furthermore, the compounds did not present cytotoxicity at concentrations up to 50 and 250 μM in MTT tests. Molecular modeling studies were conducted using DFT method (B3LYP functional and the basis set 6-311G(d,p)) to understand the activity of the compounds, corroborating the observed cruzain inhibitory activity. In docking studies, the obtained analogs showed good complementarity with cruzain active site. In addition, docking results are in accordance with the susceptibility of these analogs to nucleophilic attack of the catalytic Cys25. Taken together, this study shows that this class of compounds can be used as a prototype in the identification of new antichagasic drugs.

Hologram quantitative structure-activity relationship and comparative molecular interaction field analysis of aminothiazole and thiazolesulfonamide as reversible LSD1 inhibitors.

BACKGROUNDnLSD-1 is an enzyme that removes methyl groups from lysine residues of histone proteins. LSD-1 inhibition decreases cellular proliferation and therefore represents a therapeutic target for cancer treatment. MAO and LSD-1 are both flavin adenine dinucleotide-dependent MAOs, and the MAO inhibitor, tranylcypromine, is currently undergoing clinical trials for cancer treatment because it acts as an irreversible LSD-1 inhibitor.nnnMATERIALS & METHODSnThe present study investigated new reversible LSD-1 inhibitors, in order to develop novel selective anticancer agents. We constructed 2 and 3D quantitative structure-activity relationship models by using a series of 54 aminothiazole and thiazolesulfonamide derivatives.nnnRESULTSnThe models were validated internally and externally (q(2) , 0.691 and 0.701; r(2) , 0.894 and 0.937; r(2) test , 0.785 and 0.644, for 2 and 3D models, respectively). Fragment contribution maps, as well as steric and electrostatic contour maps were generated in order to obtain chemical information related to LSD-1 inhibition.nnnCONCLUSIONnThe thiazolesulfonamide group was fundamental to the inhibition of LSD-1 by these compounds and that bulky and aromatic substituents at the thiazole ring were important for their steric and electrostatic interactions with the active site of LSD-1.

Synthesis of two ‘heteroaromatic rings of the future’ for applications in medicinal chemistry

In a computational study, the 1H-pyrazolo[3,4-c]pyridin-5-ol and 2,6-naphthyridin-3-ol heterocycles were identified as unknown heteroaromatic ring systems of potential value for medicinal chemistry. Here we report robust and concise synthetic protocols that provide access to these two scaffolds on a multigram scale.