David M. Rogers

Bio: David M. Rogers is an academic researcher from National Center for Computational Sciences. The author has contributed to research in topics: Solvation & Excited state. The author has an hindex of 26, co-authored 102 publications receiving 2775 citations. Previous affiliations of David M. Rogers include University of Edinburgh & NewYork–Presbyterian Hospital.

Very fast prediction and rationalization of pKa values for protein-ligand complexes.

Abstract: The PROPKA method for the prediction of the pK(a) values of ionizable residues in proteins is extended to include the effect of non-proteinaceous ligands on protein pK(a) values as well as predict the change in pK(a) values of ionizable groups on the ligand itself. This new version of PROPKA (PROPKA 2.0) is, as much as possible, developed by adapting the empirical rules underlying PROPKA 1.0 to ligand functional groups. Thus, the speed of PROPKA is retained, so that the pK(a) values of all ionizable groups are computed in a matter of seconds for most proteins. This adaptation is validated by comparing PROPKA 2.0 predictions to experimental data for 26 protein-ligand complexes including trypsin, thrombin, three pepsins, HIV-1 protease, chymotrypsin, xylanase, hydroxynitrile lyase, and dihydrofolate reductase. For trypsin and thrombin, large protonation state changes (|n| > 0.5) have been observed experimentally for 4 out of 14 ligand complexes. PROPKA 2.0 and Klebe's PEOE approach (Czodrowski P et al. J Mol Biol 2007;367:1347-1356) both identify three of the four large protonation state changes. The protonation state changes due to plasmepsin II, cathepsin D and endothiapepsin binding to pepstatin are predicted to within 0.4 proton units at pH 6.5 and 7.0, respectively. The PROPKA 2.0 results indicate that structural changes due to ligand binding contribute significantly to the proton uptake/release, as do residues far away from the binding site, primarily due to the change in the local environment of a particular residue and hence the change in the local hydrogen bonding network. Overall the results suggest that PROPKA 2.0 provides a good description of the protein-ligand interactions that have an important effect on the pK(a) values of titratable groups, thereby permitting fast and accurate determination of the protonation states of key residues and ligand functional groups within the binding or active site of a protein.

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

Abstract: We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

Optimizing radionuclide sequestration in anion nanotraps with record pertechnetate sorption.

Abstract: The elimination of specific contaminants from competitors poses a significant challenge. Rather than relying on a single direct interaction, the cooperation of multiple functionalities is an emerging strategy for adsorbents design to achieve the required affinity. Here, we describe that the interaction with the target species can be altered by modifying the local environment of the direct contact site, as demonstrated by manipulating the affinity of pyridinium-based anion nanotraps toward pertechnetate. Systematic control of the substituent effect allows the resulting anion nanotraps to combine multiple features, overcoming the long-term challenge of TcO4- segregation under extreme conditions of super acidity and basicity, strong irradiation field, and high ionic strength. The top material exhibits the highest sorption capacity together with record-high extraction efficiencies after a single treatment from conditions relevant to the used nuclear fuel (Hanford tank wastes, 95%) and legacy nuclear wastes (Savannah River Sites, 80%) among materials reported thus far.

Polarization and charge transfer in the hydration of chloride ions.

Abstract: A theoretical study of the structural and electronic properties of the chloride ion and water molecules in the first hydration shell is presented. The calculations are performed on an ensemble of configurations obtained from molecular dynamics simulations of a single chloride ion in bulk water. The simulations utilize the polarizable AMOEBA force field for trajectory generation and MP2-level calculations are performed to examine the electronic structure properties of the ions and surrounding waters in the external field of more distant waters. The ChelpG method is employed to explore the effective charges and dipoles on the chloride ions and first-shell waters. The quantum theory of atoms in molecules (QTAIM) is further utilized to examine charge transfer from the anion to surrounding water molecules. The clusters extracted from the AMOEBA simulations exhibit high probabilities of anisotropic solvation for chloride ions in bulk water. From the QTAIM analysis, 0.2 elementary charges are transferred from the ion to the first-shell water molecules. The default AMOEBA model overestimates the average dipole moment magnitude of the ion compared to the quantum mechanical value. The average magnitude of the dipole moment of the water molecules in the first shell treated at the MP2-level, with the more distant waters handled with an AMOEBA effective charge model, is 2.67 D. This value is close to the AMOEBA result for first-shell waters (2.72 D) and is slightly reduced from the bulk AMOEBA value (2.78 D). The magnitude of the dipole moment of the water molecules in the first solvation shell is most strongly affected by the local water-water interactions and hydrogen bonds with the second solvation shell, rather than by interactions with the ion.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Open Babel: An open chemical toolbox

Abstract: A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats. We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org .

Ab initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields

Abstract: : The unpolarized absorption and circular dichroism spectra of the fundamental vibrational transitions of the chiral molecule, 4-methyl-2-oxetanone, are calculated ab initio. Harmonic force fields are obtained using Density Functional Theory (DFT), MP2, and SCF methodologies and a 5S4P2D/3S2P (TZ2P) basis set. DFT calculations use the Local Spin Density Approximation (LSDA), BLYP, and Becke3LYP (B3LYP) density functionals. Mid-IR spectra predicted using LSDA, BLYP, and B3LYP force fields are of significantly different quality, the B3LYP force field yielding spectra in clearly superior, and overall excellent, agreement with experiment. The MP2 force field yields spectra in slightly worse agreement with experiment than the B3LYP force field. The SCF force field yields spectra in poor agreement with experiment.The basis set dependence of B3LYP force fields is also explored: the 6-31G* and TZ2P basis sets give very similar results while the 3-21G basis set yields spectra in substantially worse agreements with experiment. jg

Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa Values.

Abstract: The new empirical rules for protein pKa predictions implemented in the PROPKA3.0 software package (Olsson et al. J. Chem. Theory Comput.2010, 7, 525–537) have been extended to the prediction of pKa shifts of active site residues and ionizable ligand groups in protein–ligand complexes. We present new algorithms that allow pKa shifts due to inductive (i.e., covalently coupled) intraligand interactions, as well as noncovalently coupled interligand interactions in multiligand complexes, to be included in the prediction. The number of different ligand chemical groups that are automatically recognized has been increased to 18, and the general implementation has been changed so that new functional groups can be added easily by the user, aided by a new and more general protonation scheme. Except for a few cases, the new algorithms in PROPKA3.1 are found to yield results similar to or better than those obtained with PROPKA2.0 (Bas et al. Proteins: Struct., Funct., Bioinf.2008, 73, 765–783). Finally, we present a n...

From Krebs to clinic: glutamine metabolism to cancer therapy.

Abstract: The resurgence of research into cancer metabolism has recently broadened interests beyond glucose and the Warburg effect to other nutrients, including glutamine. Because oncogenic alterations of metabolism render cancer cells addicted to nutrients, pathways involved in glycolysis or glutaminolysis could be exploited for therapeutic purposes. In this Review, we provide an updated overview of glutamine metabolism and its involvement in tumorigenesis in vitro and in vivo, and explore the recent potential applications of basic science discoveries in the clinical setting.