Long Time Scale Ensemble Methods in Molecular Dynamics: Ligand–Protein Interactions and Allostery in SARS-CoV-2 Targets

We subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets, 3-chymotrypsin-like protease (3CLPro), papain-like protease, and adenosine ribose phosphatase, to long time scale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10 μs simulations for each system, we accurately and reproducibly determine ligand binding sites, both crystallographically resolved and otherwise, thereby discovering binding sites that can be exploited for drug discovery. We also report robust, ensemble-based observation of conformational changes that occur at the main binding site of 3CLPro due to the presence of another ligand at an allosteric binding site explaining the underlying cascade of events responsible for its inhibitory effect. Using our simulations, we have discovered a novel allosteric mechanism of inhibition for a ligand known to bind only at the substrate binding site. Due to the chaotic nature of molecular dynamics trajectories, regardless of their temporal duration individual trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Unprecedentedly at this time scale, we compare the statistical distribution of protein-ligand contact frequencies for these ten/twelve 10 μs trajectories and find that over 90% of trajectories have significantly different contact frequency distributions. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites using long time scale simulations. The free energies differ by 0.77 to 7.26 kcal/mol across individual trajectories depending on the binding site and the system. We show that, although this is the standard way such quantities are currently reported at long time scale, individual simulations do not yield reliable free energies. Ensembles of independent trajectories are necessary to overcome the aleatoric uncertainty in order to obtain statistically meaningful and reproducible results. Finally, we compare the application of different free energy methods to these systems and discuss their advantages and disadvantages. Our findings here are generally applicable to all molecular dynamics based applications and not confined to the free energy methods used in this study

Long timescale ensemble methods in molecular dynamics: Ligand-protein interactions and allostery in SARS-CoV-2 targets

We subject a series of five protein-ligand systems which contain important SARS- CoV-2 targets - 3-chymotrypsin-like protease, papain-like protease and adenosine ribose phosphatase - to long-timescale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10-microsecond simulations for each system, we accurately and reproducibly determine ligand binding sites, both crystallographically resolved and otherwise, thereby discovering binding sites that can be exploited for drug discovery. We also report robust, ensemble-based observation of conformational changes that occur at the main binding site of 3CLPro due to the presence of another ligand at an allosteric binding site explaining the underlying cascade of events responsible for its inhibitory effect. Using our simulations, we have discovered a novel allosteric mechanism of inhibition for a ligand known to bind only at the substrate binding site. Due to the chaotic nature of molecular dynamics trajectories, individual trajectories do not allow for accurate or reproducible elucidation of macroscopic expectation values. Unprecedentedly at this timescale, we compare the statistical distribution of protein-ligand contact frequencies for these ten/twelve 10-microsecond trajectories and find that over 90% of trajectories have significantly different contact frequency distributions. Furthermore, using a direct binding free energy calculation protocol, we determine the ligand binding free energies for each of the identified sites using long-timescale simulations. The free energies differ by 0.77 to 7.26 kcal/mol across individual trajectories depending on the binding site and the system. We show that although this is the standard way such quantities are currently reported at long-timescale, individual simulations do not yield reliable free energies. Ensembles of independent trajectories are necessary to overcome the aleatoric uncertainty in order to obtain statistically meaningful and reproducible results. Our findings here are generally applicable to all molecular dynamics based applications and not confined to the free energy methods used in this study. Finally, we compare the application of different free energy methods to these systems and discuss their advantages and disadvantages

TIES 2.0: A Dual-Topology Open Source Relative Binding Free Energy Builder with Web Portal

Relative binding free energy (RBFE) calculations are widely used to aid the process of drug discovery. TIES, Thermodynamic Integration with Enhanced Sampling, is a dual-topology approach to RBFE calculations with support for NAMD and OpenMM molecular dynamics engines. The software has been thoroughly validated on publicly available datasets. Here we describe the open source software along with a web portal (https://ccs-ties.org) that enables users to perform such calculations correctly and rapidly

Geology, stratigraphy and palaeoenvironmental evolution of the Stephanorhinus kirchbergensis-bearing Quaternary palaeolake(s) of Gorzów Wielkopolski (NW Poland, Central Europe)

The sedimentary succession exposed in the Gorzów Wielkopolski area includes Eemian Interglacial (MIS 5e) or Early Weichselian (MIS 5d–e) deposits. The sedimentary sequence has been the object of intense interdisciplinary study, which has resulted in the identification of at least two palaeolake horizons. Both yielded fossil remains of large mammals, alongside pollen and plant macrofossils. All these proxies have been used to reconstruct the environmental conditions prevailing at the time of deposition, as well as to define the geological context and the biochronological position of the fauna. Optically stimulated luminescence dating of the glaciofluvial layers of the GS3 succession to 123.6 ± 10.1 (below the lower palaeolake) and 72.0 ± 5.2 ka (above the upper palaeolake) indicate that the site formed during the Middle–Late Pleistocene (MIS 6 – MIS 5). Radiocarbon-dating of the lacustrine organic matter revealed a tight cluster of Middle Pleniglacial Period (MIS 3) ages in the range of ~41–32 ka cal bp (Hengelo – Denekamp Interstadials). Holocene organic layers have also been found, with C ages within a range of 4330–4280 cal bp (Neolithic). Pollen and plant macrofossil records, together with sedimentological and geochemical data, confirm the dating to the Eemian Interglacial.This research was supported by grant 0201/2048/18 ‘Life and death of extinctrhino (Stephanorhinus sp.) from Western Poland: a multiproxy palaeoenvironmental approach’ financed by the National Science Centre, Poland. LiDAR DTM data presented in this study were used under academic licences DIO.DFT.DSI.7211.1619.2015_PL_N and DIO.DFT.7211.9874. 2015_PL_N awarded to the Faculty of Earth Sciences and the Environmental Management University of Wrocław, in accordance with the Polish legal regulations of the administration of the Head Office of Land Surveying and Cartography

Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H??????? and H???ZZ*???4??? Decay Channels at s\sqrt{s}=8??????TeV with the ATLAS Detector

Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3~fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3  fb-1 of pp collisions produced by the Large Hadron Collider at a center-of-mass energy of s=8  TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H→γγ and H→ZZ*→4ℓ event yields, which are combined accounting for detector efficiencies, fiducial acceptances, and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σpp→H=33.0±5.3 (stat)±1.6 (syst)  pb. The measurements are compared to state-of-the-art predictions.Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3 fb$^{-1}$ of $pp$ collisions produced by the Large Hadron Collider at a center-of-mass energy of $\sqrt{s} = 8$ TeV and recorded by the ATLAS detector. Cross sections are obtained from measured $H \rightarrow \gamma \gamma$ and $H \rightarrow ZZ ^{*}\rightarrow 4\ell$ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be $\sigma_{pp \to H} = 33.0 \pm 5.3 \, ({\rm stat}) \pm 1.6 \, ({\rm sys}) \mathrm{pb}$. The measurements are compared to state-of-the-art predictions