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Computational modelling of potentially emerging SARS-CoV-2 spike protein RBDs mutations with higher binding affinity towards ACE2: A structural modelling study

文献类型： 外文期刊

作者： Khan, Abbas 1 ; Hussain, Sarfaraz 2 ; Ahmad, Sajjad 3 ; Suleman, Muhammad 4 ; Bukhari, Imrana 5 ; Khan, Taimoor 1 ; Rashid, Farooq 6 ; Azad, Abul Kalam 7 ; Waseem, Muhammad 8 ; Khan, Wajid 4 ; Hussain, Zahid 4 ; Khan, Asghar 9 ; Ali, Syed Shujait 4 ; Qin, Qiyao 10 ; Wei, Dong-Qing 1 ;

作者机构： 1.Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, Dept Bioinformat & Biol Stat, Shanghai 200240, Peoples R China

2.Chinese Acad Agr Sci, Inst Food Sci & Technol, Beijing 100193, Peoples R China

3.Abasyn Univ, Dept Hlth & Biol Sci, Peshawar 25000, Pakistan

4.Univ Swat, Ctr Biotechnol & Microbiol, Swat, KP, Pakistan

5.Univ Okara, Dept Bot, Okara, Punjab, Pakistan

6.Southern Med Univ, Dermatol Hosp, Sch Publ Hlth, Dept Epidemiol, Guangzhou, Peoples R China

7.Int Islamic Univ Malaysia, Fac Pharm, Dept Pharmaceut Technol, Adv Drug Delivery Lab, Kuantan 25200, Pahang, Malaysia

8.Riphah Int Univ, Fac Rehabil & Allied Hlth Sci, Islamabad, Pakistan

9.Saidu Teaching Hosp, Swat, Khyber Pakhtunk, Pakistan

10.Renmin Univ China, Sch Stat, Beijing, Peoples R China

11.Peng Cheng Lab, Vanke Cloud City Phase 1 Bldg 8,Xili St, Shenzhen 518055, Guangdong, Peoples R China

12.Shanghai Jiao Tong Univ, State Key Lab Microbial Metab, Shanghai Islamabad Belgrade Joint Innovat Ctr Ant, Joint Lab Int Cooperat Metab & Dev Sci,Minist Edu, Shanghai 200030, Peoples R China

13.Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, Shanghai 200030, Peoples R China

关键词： SARS-CoV-2; Emerging variants; Modeling; Simulation; Free energy

期刊名称：COMPUTERS IN BIOLOGY AND MEDICINE （ 影响因子：6.698； 五年影响因子：5.752 ）

ISSN： 0010-4825

年卷期： 2022 年 141 卷

页码：

收录情况： SCI

摘要： The spike protein of SARS-CoV-2 and the host ACE2 receptor plays a vital role in the entry to the cell. Among which the hotspot residue 501 is continuously subjected to positive selection pressure and induces unusual virulence. Keeping in view the importance of the hot spot residue 501, we predicted the potentially emerging structural variants of 501 residue. We analyzed the binding pattern of wild type and mutants (Spike RBD) to the ACE2 receptor by deciphering variations in the amino acids' interaction networks by graph kernels along with evolutionary, network metrics, and energetic information. Our analysis revealed that N501I, N501T, and N501V increase the binding affinity and alter the intra and inter-residue bonding networks. The N501T has shown strong positive selection and fitness in other animals. Docking results and repeated simulations (three times) confirmed the structural stability and tighter binding of these three variants, correlated with the previous results following the global stability trend. Consequently, we reported three variants N501I, N501T, and N501V could worsen the situation further if they emerged. The relations between the viral fitness and binding affinity is a complicated game thus the emergence of high affinity mutations in the SARS-CoV-2 RBD brings up the question of whether or not positive selection favours these mutations or not?

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