@article {147302, title = {Computational Analysis of the Accumulation of Mutations in Therapeutically Important RNA Viral Proteins During Pandemics with Special Emphasis on SARS-CoV-2.}, journal = {J Mol Biol}, volume = {436}, year = {2024}, month = {2024 Jul 22}, pages = {168716}, abstract = {

Single stranded RNA viruses are primary causative agents for pandemics, causing extensive morbidity and mortality worldwide. A pivotal question in pandemic preparedness and therapeutic intervention is what are the specific mutations which are more likely to emerge during such global health crises? This study aims to identify markers for mutations with the highest probability of emergence in these pandemics, focusing on the SARS-CoV-2 spike protein, an essential and therapeutically significant viral protein, starting from sequence information from the onset of the pandemic until July 2022. Quite consistently, we observed that emerged mutations tended to demonstrate a high genetic score, which reflects high similarity of the type of codon required for translation between an amino acid and to the mutated one. Further, this pattern is also observed in therapeutically significant proteins of other ssRNA pandemic viruses, including influenza (HA, NA), spike proteins of Ebola, envelope of Dengue and Chikungunya. We propose that the genetic score serves as an initial indicator, preceding the actual impact of the mutation on viral fitness. Finally, we developed a comprehensive computational pipeline to further explore and predict the subsequent effects of mutations on viral fitness. We believe that our pipeline can narrow down and predict future mutations in therapeutically important viral proteins during a pandemic.

}, issn = {1089-8638}, doi = {10.1016/j.jmb.2024.168716}, author = {Sharma, Abhishek and Chandrashekar, C R and Krishna, Sudhir and Sowdhamini, Ramanathan} } @article {124446, title = {Bioinformatics analysis of mutations sheds light on the evolution of Dengue NS1 protein with implications in the identification of potential functional and druggable sites.}, journal = {Mol Biol Evol}, year = {2023}, month = {2023 Feb 16}, abstract = {

Non-structural protein (NS1) is a 350 amino acid long conserved protein in the dengue virus. Conservation of NS1 is expected due to its importance in dengue pathogenesis. The protein is known to exist in dimeric and hexameric states. The dimeric state is involved in its interaction with host proteins and viral replication, whereas the hexameric state is involved in viral invasion. In this work, we performed extensive structure and sequence analysis of NS1 protein, and uncovered the role of NS1 quaternary states in its evolution. A three-dimensional modeling of unresolved loop regions in NS1 structure is performed. {\textquoteright}Conserved{\textquoteright} and {\textquoteright}Variable{\textquoteright} regions within NS1 protein were identified from sequences obtained from patient samples and the role of compensatory mutations in selecting destabilizing mutations was identified. Molecular dynamics (MD) simulations were performed to extensively study the effect of a few mutations on NS1 structure stability and study compensatory mutations. Virtual saturation mutagenesis, predicting the effect of every individual amino acid substitution on NS1 stability sequentially, revealed virtual-conserved and variable sites. The increase in number of observed and virtual conserved regions across NS1 quaternary states suggests the role of higher order structure formation in its evolutionary conservation. Our sequence and structure analysis could enable in identifying possible protein-protein interfaces and druggable sites. Virtual screening of nearly 10,000 small molecules, including FDA-approved drugs, permitted us to recognize six drug-like molecules targeting the dimeric sites. These molecules could be promising due to their stable interactions with NS1 throughout the simulation.

}, issn = {1537-1719}, doi = {10.1093/molbev/msad033}, author = {Sharma, Abhishek and Krishna, Sudhir and Sowdhamini, Ramanathan} } @article {79804, title = {Computational search for potential COVID-19 drugs from FDAapproved drugs and small molecules of natural origin identifies several anti-virals and plant products.}, journal = {J Biosci}, volume = {45}, year = {2020}, month = {2020}, abstract = {

The world is currently facing the COVID-19 pandemic, for which mild symptoms include fever and dry cough. In severe cases, it could lead to pneumonia and ultimately death in some instances. Moreover, the causative pathogen is highly contagious and there are no drugs or vaccines for it yet. The pathogen, SARS-CoV-2, is one of the human coronaviruses which was identified to infect humans first in December 2019. SARS-CoV-2 shares evolutionary relationship to other highly pathogenic viruses such as Severe Acute Respiratory Syndrome (SARS) and Middle East respiratory syndrome (MERS). We have exploited this similarity to model a target non-structural protein, NSP1, since it is implicated in the regulation of host gene expression by the virus and hijacking of host machinery. We next interrogated the capacity to repurpose around 2300 FDA-approved drugs and more than 3,00,000 small molecules of natural origin towards drug identification through virtual screening and molecular dynamics. Interestingly, we observed simple molecules like lactose, previously known anti-virals and few secondary metabolites of plants as promising hits. These herbal plants are already practiced in Ayurveda over centuries to treat respiratory problems and inflammation. Disclaimer: we would not like to recommend uptake of these small molecules for suspect COVID patients until it is approved by competent national or international authorities.

}, issn = {0973-7138}, author = {Sharma, Abhishek and Tiwari, Vikas and Sowdhamini, Ramanathan} }