DataSheet1_Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum.pdf

India confines more than 17% of the world’s population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

印度国土容纳了全球超过17%的人口，并拥有多样化的遗传构成，其中包含许多与临床相关的罕见突变，这些突变属于众多亚群，在诸如1000基因组数据（1KG）等全球测序数据集中被低估，而这些数据集仅包含有限的印度族群样本。此类数据库对于制药和药物开发行业至关重要，因为多样性在识别遗传易感性方面发挥着关键作用。本研究对最近发布的最大规模印度基因组数据库（IndiGen）以及1000基因组数据中的变异信息进行了定性和比较性序列与结构研究，研究对象为激酶编码基因的变异，这是药物靶点中被靶向的第二大群体。序列层面的分析识别了基于nsSNVs和氨基酸交换频率的种群间的相似性与差异性，而IndiGen变异的比较性结构分析则与UniProtKB Humsavar数据中报道的致病性变异进行了比较。本研究探讨了这些变异对蛋白质结构特征（如结构稳定性、溶剂可及性、疏水性和氢键网络）的影响。对已知药物进行计算机模拟筛选，发现这些包含印度人口变异的蛋白质在结合强度上存在关键差异。综上所述，本研究对世界上第二大人口中普遍存在的变异进行了全面调查，并探讨了其在序列、结构和药物基因组学领域的意义。本文所报告的初步研究结果，支持对印度人群特异性ADRs进行筛选和检测，可能有助于开发针对印度人群药物相关不良事件的临床前和上市后筛查技术。