Joshi Tushar, Vijayakumar Santhiya, Ghosh Soumyadip, Mathpal Shalini, Ramaiah Sudha, Anbarasu Anand
Medical and Biological Computing Laboratory, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India.
Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore 632014, Tamil Nadu, India.
ACS Omega. 2024 Jun 14;9(26):28046-28060. doi: 10.1021/acsomega.4c00929. eCollection 2024 Jul 2.
is a highly infectious and antibiotic-resistant bacterium, which causes acute and chronic nosocomial infections. exhibits multidrug resistance due to the emergence of resistant mutants. The bacterium takes advantage of intrinsic and acquired resistance mechanisms to resist almost every antibiotic. To overcome the drug-resistance problem, there is a need to develop effective drugs against antibiotic-resistant mutants. Therefore, in this study, we selected the F533L mutation in PBP3 (penicillin-binding protein 3) because of its important role in β-lactam recognition. To target this mutation, we screened 147 antibacterial compounds from PubChem through a machine-learning model developed based on the decision stump algorithm with 75.75% accuracy and filtered out 55 compounds. Subsequently, out of 55 compounds, 47 compounds were filtered based on their drug-like activity. These 47 compounds were subjected to virtual screening to obtain binding affinity compounds. The binding affinity range of all 47 compounds was -11.3 to -4.6 kcal mol. The top 10 compounds were examined according to their binding with the mutation point. A molecular dynamic simulation of the top 8 compounds was conducted to understand the stability of the compounds containing the mutated PBP3. Out of 8 compounds, 3 compounds, namely, macozinone, antibacterial agent 71, and antibacterial agent 123, showed good stability and were validated by RMSD, RMSF, and binding-free analysis. The findings of this study revealed promising antibacterial compounds against the F533L mutant PBP3. Furthermore, developments in these compounds may pave the way for novel therapeutic interventions.
是一种具有高度传染性和抗生素抗性的细菌，可引起急性和慢性医院感染。由于抗性突变体的出现，表现出多重耐药性。该细菌利用内在和获得性抗性机制来抵抗几乎每一种抗生素。为了克服耐药性问题，需要开发针对抗生素抗性突变体的有效药物。因此，在本研究中，我们选择了PBP3（青霉素结合蛋白3）中的F533L突变，因为其在β-内酰胺识别中起重要作用。为了针对这一突变，我们通过基于决策树算法开发的机器学习模型，从PubChem中筛选了147种抗菌化合物，准确率为75.75%，并筛选出55种化合物。随后，在55种化合物中，根据它们的类药物活性筛选出47种化合物。对这47种化合物进行虚拟筛选以获得具有结合亲和力的化合物。所有47种化合物的结合亲和力范围为-11.3至-4.6 kcal/mol。根据它们与突变点的结合情况检查了前10种化合物。对前8种化合物进行了分子动力学模拟，以了解含有突变PBP3的化合物的稳定性。在8种化合物中，有3种化合物，即马佐酮、抗菌剂71和抗菌剂123，表现出良好的稳定性，并通过RMSD、RMSF和结合自由分析进行了验证。本研究结果揭示了针对F533L突变体PBP3的有前景的抗菌化合物。此外，这些化合物的开发可能为新型治疗干预铺平道路。
