Oliveira Lana P S, Lima Lúcio R, Silva Luciane B, Cruz Jorddy N, Ramos Ryan S, Lima Luciana S, Cardoso Francy M N, Silva Aderaldo V, Rodrigues Dália P, Rodrigues Gabriela S, Proietti-Junior Aldo A, Dos Santos Gabriela B, Campos Joaquín M, Santos Cleydson B R
Graduate Program in Biotechnology and Biodiversity-Network BIONORTE, Federal University of Amapá, Macapá 68903-419, Brazil.
Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, Brazil.
Pharmaceuticals (Basel). 2023 Oct 9;16(10):1430. doi: 10.3390/ph16101430.
is a microorganism with high morbidity and mortality due to antibiotic-resistant strains, making the search for new therapeutic options urgent. In this context, computational drug design can facilitate the drug discovery process, optimizing time and resources. In this work, computational methods involving ligand- and structure-based virtual screening were employed to identify potential antibacterial agents against the MRSA and VRSA strains. To achieve this goal, tetrahydroxybenzofuran, a promising antibacterial agent according to in vitro tests described in the literature, was adopted as the pivotal molecule and derivative molecules were considered to generate a pharmacophore model, which was used to perform virtual screening on the Pharmit platform. Through this result, twenty-four molecules were selected from the MolPort database. Using the Tanimoto Index on the BindingDB web server, it was possible to select eighteen molecules with greater structural similarity in relation to commercial antibiotics (methicillin and oxacillin). Predictions of toxicological and pharmacokinetic properties (ADME/Tox) using the eighteen most similar molecules, showed that only three exhibited desired properties (LB255, LB320 and LB415). In the molecular docking study, the promising molecules LB255, LB320 and LB415 showed significant values in both molecular targets. LB320 presented better binding affinity to MRSA (-8.18 kcal/mol) and VRSA (-8.01 kcal/mol) targets. Through PASS web server, the three molecules, specially LB320, showed potential for antibacterial activity. Synthetic accessibility (SA) analysis performed on AMBIT and SwissADME web servers showed that LB255 and LB415 can be considered difficult to synthesize and LB320 is considered easy. In conclusion, the results suggest that these ligands, particularly LB320, may bind strongly to the studied targets and may have appropriate ADME/Tox properties in experimental studies.
是一种因耐药菌株而具有高发病率和死亡率的微生物，这使得寻找新的治疗选择变得紧迫。在此背景下，计算机辅助药物设计可以促进药物发现过程，优化时间和资源。在这项工作中，采用了基于配体和结构的虚拟筛选的计算方法来识别针对耐甲氧西林金黄色葡萄球菌（MRSA）和耐万古霉素金黄色葡萄球菌（VRSA）菌株的潜在抗菌剂。为实现这一目标，根据文献中描述的体外试验，将一种有前景的抗菌剂四羟基苯并呋喃用作关键分子，并考虑衍生分子以生成药效团模型，该模型用于在Pharmit平台上进行虚拟筛选。通过这个结果，从MolPort数据库中选择了24个分子。使用BindingDB网络服务器上的Tanimoto指数，可以选择18个与商业抗生素（甲氧西林和苯唑西林）结构相似性更高的分子。对18个最相似分子进行毒理学和药代动力学性质（ADME/Tox）预测，结果表明只有3个表现出所需性质（LB255、LB320和LB415）。在分子对接研究中，有前景的分子LB255、LB320和LB415在两个分子靶点上都显示出显著值。LB320对MRSA（-8.18 kcal/mol）和VRSA（-8.01 kcal/mol）靶点表现出更好的结合亲和力。通过PASS网络服务器，这三个分子，特别是LB320，显示出抗菌活性的潜力。在AMBIT和SwissADME网络服务器上进行的合成可及性（SA）分析表明，LB255和LB415可能被认为难以合成，而LB320被认为易于合成。总之，结果表明这些配体，特别是LB320，可能与研究的靶点强烈结合，并且在实验研究中可能具有合适的ADME/Tox性质。
