Table11_Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum.csv

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.

印度拥有世界人口超过17%，其遗传构成多样化，包含多个亚群体中具有临床相关性的罕见突变，这些突变在全球测序数据集中未得到充分评估，如包含印度人种样本有限的1000基因组数据（1KG）。此类数据库对于制药和药物研发行业至关重要，因为多样性在识别对不良药物反应的遗传易感性方面发挥着关键作用。本研究通过利用最近发表的、最大的印度基因组数据库（IndiGen）和1000基因组数据中的变异信息，对激酶编码基因所属的变异进行了定性和比较序列及结构研究，这些激酶编码基因是药物靶标中第二多数被针对的群体。序列层面的分析识别了不同人群之间的相似性与差异，这些相似性与差异基于非同步单核苷酸多态性（nsSNVs）和氨基酸交换频率；而IndiGen变异的比较结构分析则与UniProtKB Humsavar数据中报告的致病性变异进行了比较。本研究调查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，这些药物作用于含有印度人群变异的蛋白质，揭示了由于印度人群中存在的变异而导致的结合强度的重要差异。总之，本研究对世界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景观中的影响。本文中报告的初步研究，支持针对印度人群的特定不良反应的筛选和检测，有助于开发印度人群中药物相关不良事件的临床前和上市后筛查技术。