Machine learning in the analysis of biomolecular simulations

Machine learning has rapidly become a key method for the analysis and organization of large-scale data in all scientific disciplines. In life sciences, the use of machine learning techniques is a particularly appealing idea since the enormous capacity of computational infrastructures generates terabytes of data through millisecond simulations of atomistic and molecular-scale biomolecular systems. Due to this explosion of data, the automation, reproducibility, and objectivity provided by machine learning methods are highly desirable features in the analysis of complex systems. In this review, we focus on the use of machine learning in biomolecular simulations. We discuss the main categories of machine learning tasks, such as dimensionality reduction, clustering, regression, and classification used in the analysis of simulation data. We then introduce the most popular classes of techniques involved in these tasks for the purpose of enhanced sampling, coordinate discovery, and structure prediction. Whenever possible, we explain the scope and limitations of machine learning approaches, and we discuss examples of applications of these techniques.Peer reviewe

Maturation of the SARS-CoV-2 virus is regulated by dimerization of its main protease

SARS-CoV-2 main protease (Mpro) involved in COVID-19 is required for maturation of the virus and infection of host cells. The key question is how to block the activity of Mpro. By combining atomistic simulations with machine learning, we found that the enzyme regulates its own activity by a collective allosteric mechanism that involves dimerization and binding of a single substrate. At the core of the collective mechanism is the coupling between the catalytic site residues, H41 and C145, which direct the activity of Mpro dimer, and two salt bridges formed between R4 and E290 at the dimer interface. If these salt bridges are mutated, the activity of Mpro is blocked. The results suggest that dimerization of main proteases is a general mechanism to foster coronavirus proliferation, and propose a robust drug-based strategy that does not depend on the frequently mutating spike proteins at the viral envelope used to develop vaccines. (c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer reviewe

Aquaporin 4 as a NH3 Channel

Ammonia is a biologically potent molecule, and the regulation of ammonia levels in the mammalian body is, therefore, strictly controlled. The molecular paths of ammonia permeation across plasma membranes remain ill-defined, but the structural similarity of water and NH3 has pointed to the aquaporins as putative NH3-permeable pores. Accordingly, a range of aquaporins from mammals, plants, fungi, and protozoans demonstrates ammonia permeability. Aquaporin 4 (AQP4) is highly expressed at perivascular glia end-feet in the mammalian brain and may, with this prominent localization at the blood-brain-interface, participate in the exchange of ammonia, which is required to sustain the glutamate-glutamine cycle. Here we observe that AQP4-expressing Xenopus oocytes display a reflection coefficient <1 for NH4Cl at pH 8.0, at which pH an increased amount of the ammonia occurs in the form of NH3 Taken together with an NH4Cl-mediated intracellular alkalization (or lesser acidification) of AQP4-expressing oocytes, these data suggest that NH3 is able to permeate the pore of AQP4. Exposure to NH4Cl increased the membrane currents to a similar extent in uninjected oocytes and in oocytes expressing AQP4, indicating that the ionic NH4 (+) did not permeate AQP4. Molecular dynamics simulations revealed partial pore permeation events of NH3 but not of NH4 (+) and a reduced energy barrier for NH3 permeation through AQP4 compared with that of a cholesterol-containing lipid bilayer, suggesting AQP4 as a favored transmembrane route for NH3 Our data propose that AQP4 belongs to the growing list of NH3-permeable water channels

Structural basis for maintenance of bacterial outer membrane lipid asymmetry

The Gram-negative bacterial outer membrane (OM) is a unique bilayer that forms an efficient permeation barrier to protect the cell from noxious compounds (1)(,)(2) . The defining characteristic of the OM is lipid asymmetry, with phospholipids comprising the inner leaflet and lipopolysaccharides comprising the outer leaflet (1-3) . This asymmetry is maintained by the Mla pathway, a six-component system that is widespread in Gram-negative bacteria and is thought to mediate retrograde transport of misplaced phospholipids from the outer leaflet of the OM to the cytoplasmic membrane (4) . The OM lipoprotein MlaA performs the first step in this process via an unknown mechanism that does not require external energy input. Here we show, using X-ray crystallography, molecular dynamics simulations and in vitro and in vivo functional assays, that MlaA is a monomeric α-helical OM protein that functions as a phospholipid translocation channel, forming a ~20-Å-thick doughnut embedded in the inner leaflet of the OM with a central, amphipathic pore. This architecture prevents access of inner leaflet phospholipids to the pore, but allows outer leaflet phospholipids to bind to a pronounced ridge surrounding the channel, followed by diffusion towards the periplasmic space. Enterobacterial MlaA proteins form stable complexes with OmpF/C (5,6) , but the porins do not appear to play an active role in phospholipid transport. MlaA represents a lipid transport protein that selectively removes outer leaflet phospholipids to help maintain the essential barrier function of the bacterial OM.The crystal structure of MlaA, coupled with simulations of its interaction with phospholipids, elucidates how this outer membrane lipoprotein acts as a phospholipid translocation channel to maintain the asymmetric composition of the outer membrane

Crystal Structure of an Ammonia-Permeable Aquaporin.

Aquaporins of the TIP subfamily (Tonoplast Intrinsic Proteins) have been suggested to facilitate permeation of water and ammonia across the vacuolar membrane of plants, allowing the vacuole to efficiently sequester ammonium ions and counteract cytosolic fluctuations of ammonia. Here, we report the structure determined at 1.18 Å resolution from twinned crystals of Arabidopsis thaliana aquaporin AtTIP2;1 and confirm water and ammonia permeability of the purified protein reconstituted in proteoliposomes as further substantiated by molecular dynamics simulations. The structure of AtTIP2;1 reveals an extended selectivity filter with the conserved arginine of the filter adopting a unique unpredicted position. The relatively wide pore and the polar nature of the selectivity filter clarify the ammonia permeability. By mutational studies, we show that the identified determinants in the extended selectivity filter region are sufficient to convert a strictly water-specific human aquaporin into an AtTIP2;1-like ammonia channel. A flexible histidine and a novel water-filled side pore are speculated to deprotonate ammonium ions, thereby possibly increasing permeation of ammonia. The molecular understanding of how aquaporins facilitate ammonia flux across membranes could potentially be used to modulate ammonia losses over the plasma membrane to the atmosphere, e.g., during photorespiration, and thereby to modify the nitrogen use efficiency of plants

Role of Pore-Lining Residues in Defining the Rate of Water Conduction by Aquaporin-0

Compared to other aquaporins (AQPs), lens-specific AQP0 is a poor water channel, and its permeability was reported to be pH-dependent. To date, most water conduction studies on AQP0 were performed on protein expressed in Xenopus oocytes, and the results may therefore also reflect effects introduced by the oocytes themselves. Experiments with purified AQP0 reconstituted into liposomes are challenging because the water permeability of AQP0 is only slightly higher than that of pure lipid bilayers. By reconstituting high amounts of AQP0 and using high concentrations of cholesterol to reduce the permeability of the lipid bilayer, we improved the signal-to-noise ratio of water permeability measurements on AQP0 proteoliposomes. Our measurements show that mutation of two pore-lining tyrosine residues, Tyr-23 and Tyr-149 in sheep AQP0, to the corresponding residues in the high-permeability water channel AQP1 have additive effects and together increase the water permeability of AQP0 40-fold to a level comparable to that of AQP1. Molecular dynamics simulations qualitatively support these experimental findings and suggest that mutation of Tyr-23 changes the pore profile at the gate formed by residue Arg-187

Functional assays.

<p>(A) Water permeability of liposomes with and without inserted <i>At</i>TIP2;1 measured at different pH values. Stopped-flow experiments with 100 mM hyperosmolar shift present high protein-facilitated conductivities at cytosolic and vacuolar pH. Relative single exponential rate constants of ca. 110 s⁻¹ at LPR 30 demonstrate the ability to sustain a highly water-permeable vacuole. (B) Water permeability of purified <i>At</i>TIP2;1 (LPR 50) is inhibited by mercury as previously shown in oocytes [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002411#pbio.1002411.ref021" target="_blank">21</a>]. (C) Ammonia uptake monitored by increased internal fluorescence after exchange of 20 mM NaCl with 20 mM NH₄Cl, corresponding to an initial NH₃ gradient of 4.5 μM. Proteoliposomes with <i>At</i>TIP2;1 (green) show higher permeability than equally-sized control liposomes (grey). Fitted curves yielding single exponential rates are also shown. (D) Summary of rates at different ammonia gradients. Equations and correlation coefficients are given for linear fitting of averaged single exponential rates as a function of total initial concentration gradient of NH₃/NH₄⁺. Error bars represent the standard deviation of the rate within a set of approximately ten stopped-flow recordings per liposome sample. The underlying data of panels A–D can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002411#pbio.1002411.s001" target="_blank">S1 Data</a>.</p