<i>In-silico</i> identification of fingerprint of pyrazolyl sulfonamide responsible for inhibition of <i>N</i>-myristoyltransferase using Monte Carlo method with index of ideality of correlation

Human African trypanosomiasis (HAT) or sleeping sickness like infections remain a serious health concern around the globe due to unavailability of safe and potential drugs for their treatment. Moreover, developing safe, potential and highly specific target based treatments is still a challenge for present drug discovery programs. A series of pyrazole based sulfonamides are identified as an inhibitor of <i>Trypanosoma brucei N</i>-myristoyltransferase (TbNMT). In the present manuscript, we have developed robust and reliable QSAR models by using the balance of correlation method in CORAL software. The chemical structures are represented by simplified molecular input line entry system (SMILES). The significance of the index of ideality correlation (IIC) with applicability domain (AD) is also studied at depth. The models developed by considering the index of ideality of correlation (IIC) were found to statistically more significant and robust. One QSAR model with best Rcalibration2 = 0.8638 for split 2 was considered as the leading model. A greater value of cRp² <i>i.e.</i> 0.5 for all models in Y-randomization test showed the robustness of developed models. The outliers and promoters of increase and decrease of endpoint were also extracted independently from the leading models. The mechanistic interpretation of developed models explains the role of different structural attributes in predicting the pIC₅₀ of pyrazole sulfonamides extracted from the crystal structure of Leishmania major N-myristoyltransferase (NMT) along with co-crystallized myristoyl-CoA and ligands NMT106, NMT157, NMT187 and NMT236 (PDB ID: 4A2Z, 4A30, 4A32, 2WSA). Communicated by Ramaswamy H. Sarma

非洲人类锥虫病（Human African trypanosomiasis, HAT，又称昏睡病）因缺乏安全有效的治疗药物，仍是全球范围内亟待解决的重大公共卫生问题。此外，开发安全、高效且高度特异性的靶向治疗方案，仍是当前药物研发项目面临的核心挑战。本研究中，一系列基于吡唑的磺酰胺类化合物被鉴定为布氏锥虫（Trypanosoma brucei）N-肉豆蔻酰基转移酶（TbNMT）的抑制剂。本文采用CORAL软件中的相关平衡法，构建了稳健可靠的定量构效关系（Quantitative Structure-Activity Relationship, QSAR）模型。研究以简化分子线性输入规范（Simplified Molecular Input Line Entry System, SMILES）表征化合物的化学结构，并深入探讨了理想相关指数（Index of Ideality of Correlation, IIC）与适用域（Applicability Domain, AD）的关联意义。结果表明，引入理想相关指数（IIC）构建的QSAR模型，在统计学上更具显著性与稳健性。其中，针对分组2构建的校正集决定系数$R_{calibration}^2=0.8638$的QSAR模型，被选为最优模型。Y随机化检验中，所有模型的$cR_p^2$值均达到0.5及以上，证实了所构建模型的稳健性。本研究还从最优模型中独立提取出活性终点升降的异常值与影响因子。对所建模型的机理解释，阐明了不同结构属性在预测吡唑磺酰胺类化合物的pIC₅₀值中的作用。本次研究涉及的化合物结构，提取自利什曼原虫（Leishmania major）N-肉豆蔻酰基转移酶（NMT）与共结晶肉豆蔻酰辅酶A、配体NMT106、NMT157、NMT187及NMT236的复合物晶体结构（蛋白质数据库编号PDB ID：4A2Z、4A30、4A32、2WSA）。本文由Ramaswamy H. Sarma通讯。

搜集汇总

背景与挑战

背景概述

该数据集聚焦于使用蒙特卡洛方法和理想相关性指数（IIC）开发QSAR模型，以识别吡唑基磺酰胺抑制N-肉豆蔻酰转移酶的指纹特征，针对人类非洲锥虫病（HAT）的治疗药物发现。模型基于SMILES表示化学结构，通过CORAL软件构建，统计显著性强（最佳R²为0.8638），并验证了稳健性，旨在解释结构属性对抑制活性的影响，为靶向药物设计提供计算支持。