OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration ...algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
DNA primase is an iron sulfur enzyme in DNA replication responsible for synthesizing short RNA primers that serve as starting points for DNA synthesis. The role of the 4Fe-4S cluster is not well ...determined. Here, we calculate the redox potential of the 4Fe-4S with and without DNA/RNA using continuum electrostatics. In addition, we identify the structural changes coupled to the oxidation/reduction. Our calculations show that the DNA/RNA primer lowers the redox potential by 110 and 50 mV for the 4Fe-4S+ and 4Fe-4S2+ states, respectively. The oxidation of the cluster is coupled to structural changes that significantly reduce the binding energies between the DNA and the nearby residues. The negative charges accumulated by the DNA and the RNA primers induce the oxidation of the 4Fe-4S cluster. This in turn stimulates structural changes on the DNA-protein interface that significantly reduce the binding energies.
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The novel coronavirus (nCOV-2019) outbreak has put the world on edge, causing millions of cases and hundreds of thousands of deaths all around the world, as of June 2020, let alone the societal and ...economic impacts of the crisis. The spike protein of nCOV-2019 resides on the virion’s surface mediating coronavirus entry into host cells by binding its receptor binding domain (RBD) to the host cell surface receptor protein, angiotensin converter enzyme (ACE2). Our goal is to provide a detailed structural mechanism of how nCOV-2019 recognizes and establishes contacts with ACE2 and its difference with an earlier severe acute respiratory syndrome coronavirus (SARS-COV) in 2002 via extensive molecular dynamics (MD) simulations. Numerous mutations have been identified in the RBD of nCOV-2019 strains isolated from humans in different parts of the world. In this study, we investigated the effect of these mutations as well as other Ala-scanning mutations on the stability of the RBD/ACE2 complex. It is found that most of the naturally occurring mutations to the RBD either slightly strengthen or have the same binding affinity to ACE2 as the wild-type nCOV-2019. This means that the virus had sufficient binding affinity to its receptor at the beginning of the crisis. This also has implications for any vaccine design endeavors since these mutations could act as antibody escape mutants. Furthermore, in silico Ala-scanning and long-timescale MD simulations highlight the crucial role of the residues at the interface of RBD and ACE2 that may be used as potential pharmacophores for any drug development endeavors. From an evolutional perspective, this study also identifies how the virus has evolved from its predecessor SARS-COV and how it could further evolve to become even more infectious.
Molecular dynamics (MD) simulations are now able to routinely reach timescales of microseconds and beyond. This has led to a corresponding increase in the amount of MD trajectory data that needs to ...be stored, particularly when those trajectories contain explicit solvent molecules. As such, it is desirable to be able to compress trajectory data while still retaining as much of the original information as possible. In this work, we describe compressing MD trajectory data using the NetCDF4/HDF5 file format, making use of quantization of the original positions to achieve better compression ratios. We also analyze the affect this has on both the resulting positions and the energies calculated from post‐processing these trajectories, and recommend an optimal level of quantization. Overall we find the NetCDF4/HDF5 format to be an excellent choice for storing MD trajectory data in terms of speed, compressibility, and versatility.
Among patients with diabetes and stable heart disease, those with troponin T levels of 14 ng per liter or more had a 5-year rate of cardiovascular death, MI, or stroke of 27%, versus 13% in those ...with lower levels, but received no benefit from prompt revascularization.
Cardiac troponin concentration is the preferred marker of myocardial necrosis.
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Elevated concentrations of cardiac troponin have a strong association with an adverse prognosis in patients with acute coronary syndromes and are used to identify patients who are likely to benefit from an early invasive management strategy.
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High-sensitivity assays that allow the measurement of very low cardiac troponin levels in patients with stable heart disease are now available for clinical and research use. These low, previously undetectable troponin concentrations have shown strong associations with myocardial infarction, stroke, and death in a variety of primary and secondary prevention populations, including in . . .
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm ...of partition coefficient (logP) has been developed using molecular fingerprints and a deep neural network. The machine learning model was trained on a dataset of 12,000 molecules and tested on 2000 molecules. In this article, we present our results for the blind prediction of logP for the SAMPL6 challenge. While the best submission achieved a RMSE of 0.41 logP units, our submission had a RMSE of 0.61 logP units. Overall, we ranked in the top quarter out of the 92 submissions that were made. Our results show that the deep learning model can be used as a fast, accurate and robust method for high throughput prediction of logP of small molecules.
Conformational dynamics in proteins can give rise to aggregation prone states during folding, and these kinetically stable states could form oligomers and aggregates. In this study, we investigate ...the intermediate states and near-folded states of β2-microglobulin and their physico-chemical properties using molecular dynamics and Markov state modeling. Analysis of hundreds of microseconds simulation show the importance of the edge strands in the misfolded states that give rise to a high exposure of hydrophobic residues in the core of the protein that could initiate oligomerization and aggregate formation. Our study sheds light on the first step of aggregation of β2m monomers and gave a better picture of the landscape of protein misfolding and aggregation.
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