Robert Malmstrom

Ligand-induced protein allostery plays a central role in modulating cellular signalling
pathways. Here using the conserved cyclic nucleotide-binding domain of protein kinase
A’s (PKA) regulatory subunit as a prototype signalling unit, we combine long-timescale,
all-atom molecular dynamics simulations with Markov state models to elucidate the
conformational ensembles of PKA’s cyclic nucleotide-binding domain A for the cAMP-free
(apo) and cAMP-bound states. We find that both… Show more

Ligand-induced protein allostery plays a central role in modulating cellular signalling
pathways. Here using the conserved cyclic nucleotide-binding domain of protein kinase
A’s (PKA) regulatory subunit as a prototype signalling unit, we combine long-timescale,
all-atom molecular dynamics simulations with Markov state models to elucidate the
conformational ensembles of PKA’s cyclic nucleotide-binding domain A for the cAMP-free
(apo) and cAMP-bound states. We find that both systems exhibit shallow free-energy
landscapes that link functional states through multiple transition pathways. This observation
suggests conformational selection as the general mechanism of allostery in this canonical
signalling domain. Further, we expose the propagation of the allosteric signal through key
structural motifs in the cyclic nucleotide-binding domain and explore the role of kinetics in its
function. Our approach integrates disparate lines of experimental data into one cohesive
framework to understand structure, dynamics and function in complex biological systems. Show less

Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling… Show more

Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling molecular dynamics simulations and Markov state models in the study of functional proteins. Using recent studies as a framework, we explore progress in sampling, model building, model selection, and coarse-grained analysis of models. Our goal is to highlight some of the current challenges in applying Markov state models to realistically sized proteins and spur discussion on advances in the field. Show less

We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computation Resource (NBCR). The main workflow components include: file-management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission, serial and parallel execution, and monitoring on relevant high-performance computing (HPC) resources, receptor… Show more

We describe the development of automated workflows that support computed-aided drug discovery (CADD) and molecular dynamics (MD) simulations and are included as part of the National Biomedical Computation Resource (NBCR). The main workflow components include: file-management tasks, ligand force field parameterization, receptor-ligand molecular dynamics (MD) simulations, job submission, serial and parallel execution, and monitoring on relevant high-performance computing (HPC) resources, receptor structural clustering, virtual screening (VS), and statistical analyses of the VS results. The workflows aim to standardize simulation and analysis and promote best practices within the molecular simulation and CADD communities. Each component is developed as a stand-alone workflow, which should allow for easy integration into larger frameworks built suiting user needs, while remaining intuitive and easy to extend. Show less

This study investigated the cytotoxicity of 55 species of plants. Each plant was rated as medicinal, or nonmedicinal based on the existing literature. About 79% of the medicinal plants showed some cytotoxicity, while 75% of the nonmedicinal plants showed bioactivity. It appears that Asteraceae, Labiatae, Pinaceae, and Chenopodiaceae were particularly active against human cervical cancer cells. Based on the literature, only three of the 55 plants have been significantly investigated for… Show more

This study investigated the cytotoxicity of 55 species of plants. Each plant was rated as medicinal, or nonmedicinal based on the existing literature. About 79% of the medicinal plants showed some cytotoxicity, while 75% of the nonmedicinal plants showed bioactivity. It appears that Asteraceae, Labiatae, Pinaceae, and Chenopodiaceae were particularly active against human cervical cancer cells. Based on the literature, only three of the 55 plants have been significantly investigated for cytotoxicity. It is clear that there is much toxicological work yet to be done with both medicinal and nonmedicinal plants. Show less

Virtual screening of small molecule databases against macromolecular targets was used to identify binding ligands and predict their lowest energy bound conformation (i.e., pose). AutoDock4- generated poses were rescored using mean-field pathway decoupling free energy of binding calculations and evaluated if these calculations improved virtual screening discrimination between bound and non-bound ligands. Two small molecule databases were used to evaluate the effectiveness of the rescoring… Show more

Virtual screening of small molecule databases against macromolecular targets was used to identify binding ligands and predict their lowest energy bound conformation (i.e., pose). AutoDock4- generated poses were rescored using mean-field pathway decoupling free energy of binding calculations and evaluated if these calculations improved virtual screening discrimination between bound and non-bound ligands. Two small molecule databases were used to evaluate the effectiveness of the rescoring algorithm in correctly identifying binders of L99A T4 lysozyme. Self-dock calculations of a database containing compounds with known binding free energies and co-crystal structures largely reproduced experimental measurements, although the mean difference between calculated and experimental binding free energies increased as the predicted bound poses diverged from the experimental poses. In addition, free energy rescoring was more accurate than AutoDock4 scores in discriminating between known binders and non-binders, suggesting free energy rescoring could be a useful approach to reduce false positive predictions in virtual screening experiments. Show less

Dengue virus (DENV), a member of the family Flaviviridae, presents a tremendous threat to global health since an estimated 2.5 billion people worldwide are at risk for epidemic transmission. DENV infections are primarily restricted to sub-tropical and tropical regions; however, there is concern that the virus will spread into new regions including the United States. There are no approved antiviral drugs or vaccines to combat dengue infection, although DENV vaccines have entered Phase 3 clinical… Show more

Dengue virus (DENV), a member of the family Flaviviridae, presents a tremendous threat to global health since an estimated 2.5 billion people worldwide are at risk for epidemic transmission. DENV infections are primarily restricted to sub-tropical and tropical regions; however, there is concern that the virus will spread into new regions including the United States. There are no approved antiviral drugs or vaccines to combat dengue infection, although DENV vaccines have entered Phase 3 clinical trials. Drug discovery and development efforts against DENV and other viral pathogens must overcome specificity, efficacy, safety, and resistance challenges before the shortage of licensed drugs to treat viral infections can be relieved. Current drug discovery methods are largely inefficient and thus relatively ineffective at tackling the growing threat to public health presented by emerging and remerging viral pathogens. This review discusses current and newly implemented structure-based computational efforts to discover antivirals that target the DENV NS3 protease, although it is clear that these computational tools can be applied to most disease targets. Show less

Dengue virus belongs to the family Flaviviridae and is a major emerging pathogen for which the development of vaccines and antiviral therapy has seen little success. The NS3 viral protease is a potential target for antiviral drugs since it is required for virus replication. The goal of this study was to identify novel dengue virus (type 2; DEN2V) protease inhibitors for eventual development as effective anti-flaviviral drugs. The EUDOC docking program was used to computationally screen a… Show more

Dengue virus belongs to the family Flaviviridae and is a major emerging pathogen for which the development of vaccines and antiviral therapy has seen little success. The NS3 viral protease is a potential target for antiviral drugs since it is required for virus replication. The goal of this study was to identify novel dengue virus (type 2; DEN2V) protease inhibitors for eventual development as effective anti-flaviviral drugs. The EUDOC docking program was used to computationally screen a small-molecule library for compounds that dock into the P1 pocket and the catalytic site of the DEN2V NS3 protease domain apo-structure (Murthy et al., 1999) and the Bowman-Birk inhibitor-bound structure (Murthy et al., 2000). The top 20 computer–identified hits that demonstrated the most favorable scoring “energies” were selected for in vitro assessment of protease inhibition. Preliminary protease activity assays demonstrated that more than half of the tested compounds were soluble and exhibited in vitro inhibition of the DEN2V protease. Two of these compounds also inhibited viral replication in cell culture experiments, and thus are promising compounds for further development. Show less

The alphavirus nsP2 protease is essential for correct processing of the alphavirus nonstructural polyprotein (nsP1234) and replication of the viral genome. We have combined molecular dynamics simulations with our structural studies to reveal features of the nsP2 protease catalytic site and S1′–S4 subsites that regulate the specificity of the protease. The catalytic mechanism of the nsP2 protease appears similar to the papain-like cysteine proteases, with the conserved catalytic dyad forming a… Show more

The alphavirus nsP2 protease is essential for correct processing of the alphavirus nonstructural polyprotein (nsP1234) and replication of the viral genome. We have combined molecular dynamics simulations with our structural studies to reveal features of the nsP2 protease catalytic site and S1′–S4 subsites that regulate the specificity of the protease. The catalytic mechanism of the nsP2 protease appears similar to the papain-like cysteine proteases, with the conserved catalytic dyad forming a thiolate-imidazolium ion pair in the nsP2-activated state. Substrate binding likely stabilizes this ion pair. Analysis of bimolecular complexes of Venezuelan equine encephalitis virus (VEEV) nsP2 protease with each of the nsP1234 cleavage sites identified protease residues His510, Ser511, His546 and Lys706 as critical for cleavage site recognition. Homology modelling and molecular dynamics simulations of diverse alphaviruses and their cognate cleavage site sequences revealed general features of substrate recognition that operate across alphavirus strains as well as strain specific covariance between binding site and cleavage site residues. For instance, compensatory changes occurred in the P3 and S3 subsite residues to maintain energetically favourable complementary binding surfaces. These results help explain how alphavirus nsP2 proteases recognize different cleavage sites within the nonstructural polyprotein and discriminate between closely related cleavage targets. Show less