What is life?

Reflections upon a new definition of life

What is life? Multiple definitions have been proposed to answer this question, but unfortunately, none of them has reached the consensus of the scientific community. Here, the strategy used to define what life is was based on first establishing which characteristics are common to all living systems (organic nature, entropy-producing system, self-organizing, reworkable pre-program, capacity to interact and adapt, reproduction and evolution) and from them constructing the definition taking into account that reproduction and evolution are not essential for life. On this basis, life is defined as an interactive process occurring in entropy-producing, adaptive, and informative (organic) systems. An unforeseen consequence of the inseparable duality between the system (living being) and the process (life) is the interchangeability of the elements of the definition to obtain other equally valid alternatives. In addition, in the light of this definition, cases of temporarily lifeless living systems (viruses, dormant seeds, and ultracold cells) are analyzed, as well as the status of artificial life entities and the hypothetical nature of extraterrestrial life. All living systems are perishable because the passage of time leads to increasing entropy. Life must create order by continuously producing disorder and exporting it to the environment and so we move and stay in the phase transition between order and chaos, far from equilibrium, thanks to the input of energy from the outside. However, the passage of time eventually leads us to an end in which life disappears and entropy increases.

Target-based virtual screening, computational multiscoring docking and molecular dynamics simulation of small molecules as promising drug candidate affecting kinesin-like protein KIFC1

The kinesin family member C1 (KIFC1) is an essential protein that facilitates the bipolar division of neoplastic cells. Inhibiting KIFC1 by small molecules is a lucrative strategy to impede bipolar mitosis leading to the apoptosis of cancerous cells. The research aims to envisage small-molecule inhibitors targeting KIFC1. The Mcule database, a comprehensive online digital platform containing more than five million chemical compounds, was used for structure-based virtual screening (SBVS). Druglikeness filtration sifted 2,293,282 chemical hits that further narrowed down to 49 molecules after toxicity profiling. Finally, 39 compounds that comply with the BOILED-Egg permeation predictive model of the ADME rules were carried forward for multiscoring docking using the AutoDock Vina inbuilt to Mcule drug discovery platform, DockThor and SwissDock tools. The mean of ΔG terms produced by docking tools was computed to find consensus top ligand hits. AZ82 exhibited stronger binding (Consensus ΔG: -7.99 kcal mol^-1 ) with KIFC1 among reference inhibitors, for example, CW069 (-7.57 kcal mol^-1 ) and SR31527 (-7.01 kcal mol^-1 ). Ten ligand hits namely, Mcule-4895338547 (Consensus ΔG: -8.69 kcal mol^-1 ), Mcule-7035674888 (-8.42 kcal mol^-1 ), Mcule-5531166845 (-8.53 kcal mol^-1 ), Mcule-3248415882 (-8.55 kcal mol^-1 ), Mcule-291881733 (-8.41 kcal mol^-1 ), Mcule-5918624394 (-8.44), Mcule-3470115427 (-8.47), Mcule-3686193135 (-8.18 kcal mol^-1 ), Mcule-3955355291 (8.09 kcal mol^-1 ) and Mcule-9534899193 (-8.01 kcal mol^-1 ) depicted strong binding interactions with KIFC1 in comparison to potential reference inhibitor AZ82. The top four ligands and AZ82 were considered for molecular dynamics simulation of 50 ns duration. Toxicity profiling, physicochemical properties, lipophilicity, solubility, pharmacokinetics, druglikeness, medicinal chemistry attributes, average potential energy, RMSD, RMSF, SASA, ΔGsolv and Rg analyses forecast the ligand mcule-4895338547 as a promising inhibitor of KIFC1.