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DG-AMMOS: A New tool to generate 3D conformation of small molecules using Distance Geometry and Automated MolecularMechanics Optimization for in silico Screening

机译:DG-AMMOS:使用距离几何和自动分子力学优化进行计算机筛选的小工具生成3D构象的新工具

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Background: Discovery of new bioactive molecules that could enter drug discovery programs orthat could serve as chemical probes is a very complex and costly endeavor. Structure-based andligand-based in silico screening approaches are nowadays extensively used to complementexperimental screening approaches in order to increase the effectiveness of the process andfacilitating the screening of thousands or millions of small molecules against a biomolecular target.Both in silico screening methods require as input a suitable chemical compound collection and mostoften the 3D structure of the small molecules has to be generated since compounds are usuallydelivered in 1D SMILES, CANSMILES or in 2D SDF formats.Results: Here, we describe the new open source program DG-AMMOS which allows thegeneration of the 3D conformation of small molecules using Distance Geometry and their energyminimization via Automated Molecular Mechanics Optimization. The program is validated on theAstex dataset, the ChemBridge Diversity database and on a number of small molecules with knowncrystal structures extracted from the Cambridge Structural Database. A comparison with the freeprogram Balloon and the well-known commercial program Omega generating the 3D of smallmolecules is carried out. The results show that the new free program DG-AMMOS is a veryefficient 3D structure generator engine.Conclusion: DG-AMMOS provides fast, automated and reliable access to the generation of 3Dconformation of small molecules and facilitates the preparation of a compound collection prior tohigh-throughput virtual screening computations. The validation of DG-AMMOS on several differentdatasets proves that generated structures are generally of equal quality or sometimes better thanstructures obtained by other tested methods.
机译:背景:可以进入药物发现程序或可以用作化学探针的新生物活性分子的发现是一项非常复杂且代价高昂的工作。如今,基于结构和基于配体的计算机硅筛选方法已广泛用于补充实验筛选方法,以提高该方法的有效性并促进针对生物分子靶标筛选成千上万个小分子。两种计算机筛选方法均需要输入由于化合物通常以1D SMILES,CANSMILES或2D SDF格式提供,因此必须生成合适的化学化合物集合,并且通常必须生成小分子的3D结构。结果:在这里,我们描述了允许生成小分子的3D构象的应用,以及通过自动分子力学最优化实现的能量最小化。该程序已在Astex数据集,ChemBridge多样性数据库以及从剑桥结构数据库中提取的许多具有已知晶体结构的小分子上进行了验证。将其与生成小分子3D的自由程序Balloon和著名的商业程序Omega进行比较。结果表明,新的免费程序DG-AMMOS是一种非常高效的3D结构生成器引擎。结论:DG-AMMOS可快速,自动和可靠地访问小分子3D构象的生成,并有助于在高分子量化合物制备之前吞吐量虚拟筛选计算。 DG-AMMOS在多个不同数据集上的验证证明,生成的结构通常质量相同,有时甚至优于通过其他测试方法获得的结构。

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