Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. Supplementary information Supplementary data are available at Bioinformatics online.

Drug delivery systems may benefit from nanoparticles synthesized using biological methods. While chemical reduction of particles is facilitated by some active compounds present in the bio-extract, other active compounds, with potential therapeutic activities, may be adsorbed onto the surface of nanoparticles. However, the mechanism of bio-based nanoparticle synthesis is still under debate. Here, we first employed a molecular dynamics (MD) approach to theoretically predict the coating of a hypothetical 4.5 nm silver nanoparticle with four selected rosemary (Rosmarinus Officinalis L.) active compounds (rosmanol, isorosmanol, carnosol, and carnosic acid). Analysis of density maps and radial distribution functions (RDF) values suggested that the examined compounds had strong hydrophobic properties and could instantaneously be adsorbed to the nanoparticle surfaces. Next, we experimentally examined the capacity of rosemary leaf extract to synthesize and coat Ag-conjugated nanoparticles. The data obtained from ultraviolet-visible spectroscopy, transmission electron microscopy, Fourier-transform infrared spectroscopy and X-ray powder diffraction analyses confirmed the production of spherical Ag-conjugated nanoparticles with an average size of 12-15 nm, coated with proteins, secondary metabolites and other active compounds. Since this method can predict the dynamic behavior of therapeutic compounds when they are in contact with nanoparticles, we believe it provides a valid and new avenue to designing new therapeutic nanoparticles.

8Small molecules such as substrates, effectors and drugs play essential roles in biological 9 processes. Knowing their interactions with biomacromolecular targets demands a deep 10 understanding of binding and unbinding mechanisms. Dozens of papers have suggested that 11 discovering of either binding or unbinding events by means of conventional UMD simulation 12 urges a considerable amount of computational resources, therefore, only one who holds a 13 supercomputer can afford such extensive simulations. Capabilities of full atomistic Unbiased 14 Molecular Dynamics (UMD) simulation have been undervalued within the scientific community. 15 Thus, myriads of researchers are impelled to be content with debatable biased MD simulations 16 which seek validation for its preconceived framework. In this work, we present a stratagem to 17 empower everyone to perform UMD simulations of protein-ligand binding and unbinding by 18 typical desktop computers and achieve valuable and high-cost results in nanosecond time scale. 19 Here, we have described kinetics of binding and unbinding of anticancer drug, dasatinib, to c-Src 20 kinase in full atomistic details for the first time. We have attained multiple independent binding 21 and unbinding events occurred in the nano-second timescale, even in times as little as 30 and 22 392.6 ns respectively, without presence of any biasing forces, an achievement that nobody has 23 ever assumed to be possible. 24 Ligand binding and unbinding pathway, Dasatinib, c-Src kinase 26 27 28Small molecule compounds are involved in nearly all cellular mechanisms and studying 29 their roles can unravel secrets behind the scenes. These compounds can trigger cell signaling and 30 metabolic pathways by interacting and binding to certain biomacromolecules like proteins and 31 nucleic acids. Over the last few decades, sophisticated methods such as X-ray crystallography, 32 NMR and electron microscopy revealed numerous structural details of many protein-ligand 33 complexes. However, these complexes are just one or some static poses of a vivid system which 34 its function is completely swayed by its movements and dynamics. Furthermore, in many 35 molecular targets like androgen receptor (PDB ID: 2Q7I) 1 , the binding pocket is buried deep 36 inside the protein structure. The X-ray crystallographic structure doesn't reveal any details about 37 the process of induction and the binding pathway, how the ligand makes an entrance into the 38 protein and how it affects residues on its journey to reach the native binding pose. According to 39 the Food and Drug Administration (FDA), small molecules make up the main proportion of 40 approved drugs on the pharmaceutical market today. Thus, understanding the induction and 41 binding mechanisms of small molecules to their molecular targets can immensely assist 42 researchers to optimize and design much more specific and selective drugs accompanied by 43 extremely low side-effects. Therefore, emergence of a complementary method which can take 44 the advantages of ...

11Understanding the details of unbinding mechanism of small molecule drugs is an 12 inseparable part of rational drug design. Reconstruction of the unbinding pathway of small 13 molecule drugs, todays, can be achieved through molecular dynamics simulations. Nonetheless, 14 simulating a process in which a drug unbinds from its receptor demands lots of time, mostly up 15 to several milliseconds. This amount of time is neither reasonable nor affordable; therefore, 16 many researchers utilize various biases that there are still many doubts about their 17 trustworthiness. In this work we have utilized short-run simulations, replicas, to make such time-18 consuming process cost effective. By replicating those snapshots of the trajectories which, after 19 careful analyses, were selected as potential candidates we increased our system's efficiency 20 considerably. As a matter of fact, we have implemented a sort of human bias, inspecting 21 trajectories visually, to achieve multiple unbinding events. We would like to call this stratagem, 22 replicating of potent snapshots, "rational sampling" as it is, in fact, benefiting from human logic. 23In our case, an anticancer drug, the dasatinib, completely unbounded from its target protein, c-24 Src kinase, in only 392.6 ns, and this was gained without applying any internal biases and 25 potentials which can increase error level. Thus, we achieved important structural details that can 26 alter our viewpoint as well as assist drug designers. 27 2

The HTLV-1 protease is one of the major antiviral targets to overwhelm this virus. Several research groups have developed protease inhibitors, but none has been successful. In this regard, developing new HTLV-1 protease inhibitors to fix the defects in previous inhibitors may overcome the lack of curative treatment for this oncovirus. Thus, we decided to study the unbinding pathways of the most potent (compound 10, PDB ID 4YDF, Ki = 15 nM) and one of the weakest (compound 9, PDB ID 4YDG, Ki = 7900 nM) protease inhibitors, which are very structurally similar. We conducted 12 successful short and long simulations (totaling 14.8 μs) to unbind the compounds from two monoprotonated (mp) forms of protease using the Supervised Molecular Dynamics (SuMD) without applying any biasing force. The results revealed that Asp32 or Asp32′ in the two forms of mp state similarly exert powerful effects on maintaining both potent and weak inhibitors in the binding pocket of HTLV-1 protease. In the potent inhibitor’s unbinding process, His66′ was a great supporter that was absent in the weak inhibitor’s unbinding pathway. In contrast, in the weak inhibitor’s unbinding process, Trp98/Trp98′ by pi-pi stacking interactions were unfavorable for the stability of the inhibitor in the binding site. In our opinion, these results will assist in designing more potent and effective inhibitors for the HTLV-1 protease.