The ubiquitous presence of wrinkles in two-dimensional materials alters their properties significantly. It is observed that during the growth process of graphene, water molecules, sourced from ambient humidity or transferred method used, can get diffused in between graphene and the substrate. The water diffusion causes/assists wrinkle formation in graphene, which influences its properties. The diffused water eventually dries, altering the geometrical parameters and properties of wrinkled graphene nanoribbons. Our study reveals that the initially distributed wrinkles tend to coalesce to form a localized wrinkle whose configuration depends on the initial wrinkle geometry and the quantity of the diffused water. The movement of the localized wrinkle is categorized into three modes—bending, buckling, and sliding. The sliding mode is characterized in terms of velocity as a function of diffused water quantity. Direct bandgap increases linearly with the initial angle except the highest angle considered (21°), which can be attributed to the electron tunneling effect observed in the orbital analysis. The system becomes stable with an increase in the initial angle of wrinkle as observed from the potential energy plots extracted from MD trajectories and confirmed with the DOS plot. The maximum stress generated is less than the plastic limit of the graphene.

A micro-molecule of dimension 125 nm has caused around 479 million human infections (80 M for the USA) and 6.1 million human deaths (977,000 for the USA) worldwide and slashed the global economy by US$ 8.5 Trillion over two years period. The only other events in recent history that caused comparative human life loss through direct usage (either by human or nature, respectively) of structure-property relations of 'nano-structures' (either human-made or nature, respectively) were nuclear bomb attacks during World War II and 1918 Flu Pandemic. This molecule is called SARS-CoV-2, which causes a disease known as COVID-19. The high liability cost of the pandemic had incentivized various private, government, and academic entities to work towards finding a cure for this and emerging diseases. As an outcome, multiple vaccine candidates are discovered to avoid the infection in the first place. But so far, there has been no success in finding fully effective therapeutic candidates. In this paper, we attempted to provide multiple therapy candidates based upon a sophisticated multi-scale in-silico framework, which increases the probability of the candidates surviving an in-vivo trial. We have selected a group of ligands from the ZINC database based upon previously partially successful candidates, i.e., Hydroxychloroquine, Lopinavir, Remdesivir, Ritonavir. We have used the following robust framework to screen the ligands; Step-I: high throughput molecular docking, Step-II: molecular dynamics analysis, Step-III: density functional theory analysis. In total, we have analyzed 242,000(ligands)*9(proteins) = 2.178 million unique protein binding site/ligand combinations. The proteins were selected based on recent experimental studies evaluating potential inhibitor binding sites. Step-I had filtered that number down to 10 ligands/protein based on molecular docking binding energy, further screening down to 2 ligands/protein based on drug-likeness analysis. Additionally, these two ligands per protein were analyzed in Step-II with a molecular dynamic modeling-based RMSD filter of less than 1Å. It finally suggested three ligands (ZINC001176619532, ZINC000517580540, ZINC000952855827) attacking different binding sites of the same protein(7BV2), which were further analyzed in Step-III to find the rationale behind comparatively higher ligand efficacy. Supplementary Information The online version contains supplementary material available at 10.1007/s10853-022-07195-8.

Chronic levels of inflammation lead to autoimmune diseases such as rheumatoid arthritis and atherosclerosis. A key molecular mediator responsible for the progression of these diseases is Chemokine C–C motif ligand 2 (CCL2), a homodimerized cytokine that dissociates into monomeric form and binds to the CCR2 receptor. CCL2, also known as monocyte chemoattractant protein‐1 (MCP‐1), attracts monocytes to migrate to areas of injury and mature into macrophages, leading to positive feedback inflammation with further release of proinflammatory molecules such as IL‐1β and TNF‐α. Sequestering CCL2 to prevent its binding to CCR2 may prevent this inflammatory activity. Prior work adapted an α‐helical CCL2‐binding peptide (WKNFQTI) from murine CCR2 through extracellular loop analysis. Here, higher‐affinity peptide binders are computationally designed through homology modeling and energy calculations, yielding an 11‐amino acid peptide with high binding affinity. In addition, Rosetta mutations improves binding affinity in silico with blockage of the CCL2 dimerization site. Future work in analyzing binding kinetics and in vivo inflammation abrogation will confirm the accuracy of computational modeling techniques in de novo rational design of CCL2 cytokine binders.

Search of life elsewhere in the galaxy is very fascinating area for planetary scientists and astrobiologists. Earth Similarity Index (ESI) is defined as geometrical mean of four physical parameters (Such as radius, density, escape velocity and surface temperature), which is ranging from 1 (identical to Earth) to 0 (dissimilar to Earth). In this work, ESI is re-defined as six parameters by introducing the two new physical parameters like revolution and surface gravity and is called as New Earth Similarity Index (NESI). The main focus of this paper is to search Tardigrade water-life on exoplanets by varying the temperature parameter in NESI, which is called as Tardigrade Similarity Index (TSI), which is ranging from 1 (Tardigrade can survive) to 0 (Tardigrade Cannot survive). Here the NESI and TSI is cataloged and analyzed for almost 3370 confirmed exoplanets.

Graphene-water interaction has been under scrutiny ever since graphene discovery and realization of its exceptional properties. Several computational and experimental reports exist that have tried to look into the interactions involved, however, none of them addresses the issue in its entirety. Most computational analysis doesn't go beyond the atomistic scale and report graphene to be hydrophobic. Meanwhile, several experimental and molecular dynamics (MD) studies show an active interaction between graphene and water. We have, therefore, tested the inherent hydrophobic behavior of a small graphene in water droplet by the means of MD simulations. The analysis has been extended to multiple graphene flakes in water and their respective size dependent responses to water droplet. Graphene retreats from water droplet to encapsulate it from the surface. This response was highly dependent upon graphene size with respect to water content. Additionally, we also report self-assembly of multilayered graphene in water by means of MD simulations, an observation which can be utilized to synthesize such structures in a cost-effective way by experimentalists. To fully comprehend graphene behavior in water, graphene deformation was analyzed in the presence of water molecules. It was noticed that graphene wrinkled to wrap around water molecules and resisted complete failure, one that is seen in case of a sole graphene sheet. Our work will not only address the question about whether graphene is hydrophobic or hydrophilic but also provide insight into the behavior of graphene surface and mobility when exposed to water which can be exploited in numerous applications.