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The human ether-à-go-go-related potassium channel (hERG) is a voltage-gated potassium channel involved in the repolarization of the cardiac action potential. The off-target inhibition of hERG is the most frequent cause of drug-induced cardiotoxicity. Therefore, assessing hERG related cardiotoxicity in the early phase of the drug discovery process is crucial to avoid undesired cardiotoxic effects. For this purpose, we developed several machine learning classification models for hERG liability profiling basing on Random Forest algorithm by means of Weka software. The models were trained on a dataset of molecules collected from the public repository ChEMBL (https://www.ebi.ac.uk/chembl/) and the commercial GOSTAR database (https://www.gostardb.com/). The training molecules were encoded by both ligand- and structure-based attributes. The former consist of a set of physicochemical descriptors and fingerprints computed by RDKit node available in KNIME, while the latter comprise different scores obtained by docking and rescoring calculations performed by LiGen and Rescore+ tools, respectively. The following models are made available: hERG_LB, trained on ligand-based descriptors hERG_LiGen_AV, trained on a set of scores computed on the docking poses yielded by LiGen, considering for each score the mean value over all the computed poses. hERG_LiGen_AV-LB, trained on the combination of the descriptors used to build hERG_LB and hERG_LiGen_AV-LB models. The input datasets used for the models training and evaluation are made available too. &nbsp

Antibiotic resistance is a major threat to global public health. β-lactamases, which catalyze breakdown of β-lactam antibiotics, are a principal cause. Metallo β-lactamases (MBLs) represent a particular challenge because they hydrolyze almost all β-lactams and to date no MBL inhibitor has been approved for clinical use. Molecular simulations can aid drug discovery, for example, predicting inhibitor complexes, but empirical molecular mechanics (MM) methods often perform poorly for metalloproteins. Here we present a multiscale approach to model thiol inhibitor binding to IMP-1, a clinically important MBL containing two catalytic zinc ions, and predict the binding mode of a 2-mercaptomethyl thiazolidine (MMTZ) inhibitor. Inhibitors were first docked into the IMP-1 active site, testing different docking programs and scoring functions on multiple crystal structures. Complexes were then subjected to molecular dynamics (MD) simulations and subsequently refined through QM/MM optimization with a density functional theory (DFT) method, B3LYP/6-31G(d), increasing the accuracy of the method with successive steps. This workflow was tested on two IMP-1:MMTZ complexes, for which it reproduced crystallographically observed binding, and applied to predict the binding mode of a third MMTZ inhibitor for which a complex structure was crystallographically intractable. We also tested a 12-6-4 nonbonded interaction model in MD simulations and optimization with a SCC-DFTB QM/MM approach. The results show the limitations of empirical models for treating these systems and indicate the need for higher level calculations, for example, DFT/MM, for reliable structural predictions. This study demonstrates a reliable computational pipeline that can be applied to inhibitor design for MBLs and other zinc-metalloenzyme systems.

Molecules : a journal of synthetic chemistry and natural product chemistry 26(4), 797 (2021). doi:10.3390/molecules26040797 special issue: "Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics / Special Issue Editors: Dr. Marco Tutone, Guest Editor; Prof. Dr. Anna Maria Almerico, Guest Editor", Published by Springer, Berlin ; Heidelberg

(1) Background: Virtual screening studies on the therapeutically relevant proteins of the severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) require a detailed characterization of their druggable binding sites, and, more generally, a convenient pocket mapping represents a key step for structure-based in silico studies, (2) Methods: Along with a careful literature search on SARS-CoV-2 protein targets, the study presents a novel strategy for pocket mapping based on the combination of pocket (as performed by the well-known FPocket tool) and docking searches (as performed by PLANTS or AutoDock/Vina engines), such an approach is implemented by the Pockets 2.0 plug-in for the VEGA ZZ suite of programs, (3) Results: The literature analysis allowed the identification of 16 promising binding cavities within the SARS-CoV-2 proteins and the here proposed approach was able to recognize them showing performances clearly better than those reached by the sole pocket detection, and (4) Conclusions: Even though the presented strategy should require more extended validations, this proved successful in precisely characterizing a set of SARS-CoV-2 druggable binding pockets including both orthosteric and allosteric sites, which are clearly amenable for virtual screening campaigns and drug repurposing studies. All results generated by the study and the Pockets 2.0 plug-in are available for download.

O Projeto Esporte Brasil (PROESP-Br) propõe, desde 1994, uma bateria de medidas e testes para avaliação de escolares entre seis e 17 anos com o objetivo de delinear o perfil de crianças e jovens brasileiros no que se refere a aptidão física relacionada à saúde e ao desempenho motor. O objetivo deste estudo foi delinear o perfil da aptidão física de crianças e jovens brasileiros a partir de uma revisão sistemática da literatura sobre artigos que utilizaram da proposta do PROESP-Br. A busca foi realizada na PubMed, ScienceDirect, Lilacs, SciELO e Google Acadêmico. Estudos originais publicados entre 1994 e 2017 acerca da aptidão física (saúde e/ou desempenho motor) de escolares (crianças e/ou adolescentes) que utilizaram a bateria de testes do PROESP-Br foram incluídos. Um total de 13.582 sujeitos foram avaliados quanto a saúde e 276 quanto ao desempenho motor nos 18 estudos incluídos. A qualidade metodológica foi avaliada uma versão adaptada da Newcastle-Ottawa quality assessment scale. Os resultados evidenciam que 27-30% dos jovens estão na “zona de risco” à saúde para o Índice de Massa Corporal (IMC), 70% para a aptidão cardiorrespiratória (ApC) e 50 e 65% para flexibilidade e força muscular localizada (FML), respectivamente. Os dados sobre o desempenho motor são inconsistentes nesta revisão de literatura. Em síntese, os resultados indicam baixos níveis de saúde cardiovascular (IMC/ApC), principalmente quanto à ApC, assim como baixos níveis de saúde musculoesquelética (flexibilidade/FML) dos jovens. Ressalta-se a escassez de estudos quanto ao desempenho motor impossibilitando delinear o perfil dos componentes deste construto. Since 1994, the Projeto Esporte Brasil (PROESP-Br) battery tests has been used to evaluate healthand skill-related physical fitness among aged 6-17 Brazilian schoolchildren. The aim of this study was to delineate the Brazilian children and youth’s physical fitness profile from a systematic review over studies that used the PROESP-Br proposal. The search was carried at PubMed, ScienceDirect, Lilacs, SciELO and Google Scholar. Original studies published between 1994 and 2017 about physical fitness (health and/or motor performance) with schoolchildren (children and/or adolescents) that used the PROESP-Br battery test were included. A total of 13.582 participants were evaluated to health-related fitness and 276 to skill-related fitness from 18 included studies. The methodological quality was evaluated using the Newcastle-Ottawa quality assessment scale adapted version. The results show that 27-30% of youngsters are at health “risk zone” for Body Mass Index (BMI), 70% for cardiorespiratory fitness (CRF), 50% and 65% for flexibility (FLEX) and muscular strength (MST), respectively. The data concerning skill-related fitness were inconsistent. In summary, the results suggest that Brazilian children and adolescents have low cardiovascular health level (BMI/ CRF), mainly regarding CRF, and low muscle health level (FLEX/MST). We emphasize that the lack of studies regarding skill-related fitness, make it impossible to describe the profile of the components of this construct.