Timothy Cholko

GeomBD3 is a robust Brownian dynamics simulation package designed to easily handle natural or engineered systems in diverse environments and arrangements. The software package described herein allows users to design, execute, and analyze BD simulations. The simulations use all-atom, rigid molecular models that diffuse according to overdamped Langevin dynamics and interact through electrostatic, Lennard-Jones, and ligand desolvation potentials. The program automatically calculates molecular association rates, surface residence times, and association statistics for any number of user-defined association criteria. Users can also extract molecular association pathways, diffusion coefficients, intermolecular interaction energies, intermolecular contact probability maps, and more using the provided supplementary analysis scripts. We detail the use of the package from start to finish and apply it to a protein–ligand system and a large nucleic acid biosensor. GeomBD3 provides a versatile tool for researchers from various disciplines that can aid in rational design of engineered systems or play an explanatory role as a complement to experiments. GeomBD version 3 is available on our website at http://chemcha-gpu0.ucr.edu/geombd3/ and KBbox at https://kbbox.h-its.org/toolbox/methods/molecular-simulation/geombd/.

Electrochemical biosensors have extremely robust applications while offering ease of preparation, miniaturization, and tunability. By adjusting the arrangement and properties of immobilized probes on the sensor surface to optimize target–probe association, one can design highly sensitive and efficient sensors. In electrochemical nucleic acid biosensors, a self-assembled monolayer (SAM) is widely used as a tunable surface with inserted DNA or RNA probes to detect target sequences. The effects of inhomogeneous probe distribution across surfaces are difficult to study experimentally due to inadequate resolution. Regions of high probe density may inhibit hybridization with targets, and the magnitude of the effect may vary depending on the hybridization mechanism on a given surface. Another fundamental question concerns diffusion and hybridization of DNA taking place on surfaces and whether it speeds up or hinders molecular recognition. We used all-atom Brownian dynamics simulations to help answer these questions by simulating the hybridization process of single-stranded DNA (ssDNA) targets with a ssDNA probe on polar, nonpolar, and anionic SAMs at three different probe surface densities. Moreover, we simulated three tightly packed probe clusters by modeling clusters with different interprobe spacing on two different surfaces. Our results indicate that hybridization efficiency depends strongly on finding a balance that allows attractive forces to steer target DNA toward probes without anchoring it to the surface. Furthermore, we found that the hybridization rate becomes severely hindered when interprobe spacing is less than or equal to the target DNA length, proving the need for a careful design to both enhance target–probe association and avoid steric hindrance. We developed a general kinetic model to predict hybridization times and found that it works accurately for typical probe densities. These findings elucidate basic features of nanoscale biosensors, which can aid in rational design efforts and help explain trends in experimental hybridization rates at different probe densities.

The Cdk8 kinase module (CKM) in Mediator, comprising Med13, Med12, CycC, and Cdk8, regulates RNA polymerase II transcription through kinase-dependent and -independent functions. Numerous pathogenic mutations causative for neurodevelopmental disorders and cancer congregate in CKM subunits. However, the structure of the intact CKM and the mechanism by which Cdk8 is non-canonically activated and functionally affected by oncogenic CKM alterations are poorly understood. Here, we report a cryo–electron microscopy structure of Saccharomyces cerevisiae CKM that redefines prior CKM structural models and explains the mechanism of Med12-dependent Cdk8 activation. Med12 interacts extensively with CycC and activates Cdk8 by stabilizing its activation (T-)loop through conserved Med12 residues recurrently mutated in human tumors. Unexpectedly, Med13 has a characteristic Argonaute-like bi-lobal architecture. These findings not only provide a structural basis for understanding CKM function and pathological dysfunction, but also further impute a previously unknown regulatory mechanism of Mediator in transcriptional modulation through its Med13 Argonaute-like features.

Amyloid-β (Aβ) plaques, which form by aggregation of harmless Aβ peptide monomers into larger fibrils, are characteristic of neurodegenerative disorders such as Alzheimer’s disease. Efforts to treat Alzheimer’s disease focus on stopping or reversing the aggregation process that leads to fibril formation. However, effective treatments are elusive due to certain unknown aspects of the process. Many hypotheses point to disruption of cell membranes by adsorbed Aβ monomers or oligomers, but how Aβ behaves and aggregates on surfaces of widely varying properties, such as those present in a cell, is unclear. Elucidating the effects of various surfaces on the dynamics of Aβ and the kinetics of the aggregation process from bulk solution to a surface-adsorbed multimer can help identify what drives aggregation, leading to new methods of intervention by inhibitory drugs or other means. In this work, we used all-atom Brownian dynamics simulations to study the association of two distinct Aβ42 monomer conformations with a surface-adsorbed or free-floating Aβ42 dimer. We calculated the association time, surface interaction energy, surface diffusion coefficient, surface residence time, and the mechanism of association on four different surfaces and two different bulk solution scenarios. In the presence of a surface, the majority of monomers underwent a two-dimensional surface-mediated association that depended primarily on an Aβ42 electrostatic interaction with the self-assembled monolayer (SAM) surfaces. Moreover, aggregation could be inhibited greatly by surfaces with high affinity for Aβ42 and heterogeneous charge distribution. Our results can be used to identify new opportunities for disrupting or reversing the Aβ42 aggregation process.

Simulations reveal the dynamic properties of freely diffusing and surface-tethered ssDNA on self-assembled monolayers with widely varying surface properties.

Abnormal activity of cyclin-dependent kinase 8 (CDK8) along with its partner protein cyclin C (CycC) is a common feature of many diseases including colorectal cancer. Using molecular dynamics (MD) simulations, this study determined the dynamics of the CDK8-CycC system and we obtained detailed breakdowns of binding energy contributions for four type-I and five type-II CDK8 inhibitors. We revealed system motions and conformational changes that will affect ligand binding, confirmed the essentialness of CycC for inclusion in future computational studies, and provide guidance in development of CDK8 binders. We employed unbiased all-atom MD simulations for 500 ns on twelve CDK8-CycC systems, including apoproteins and protein–ligand complexes, then performed principal component analysis (PCA) and measured the RMSF of key regions to identify protein dynamics. Binding pocket volume analysis identified conformational changes that accompany ligand binding. Next, H-bond analysis, residue-wise interaction calculations, and MM/PBSA were performed to characterize protein–ligand interactions and find the binding energy. We discovered that CycC is vital for maintaining a proper conformation of CDK8 to facilitate ligand binding and that the system exhibits motion that should be carefully considered in future computational work. Surprisingly, we found that motion of the activation loop did not affect ligand binding. Type-I and type-II ligand binding is driven by van der Waals interactions, but electrostatic energy and entropic penalties affect type-II binding as well. Binding of both ligand types affects protein flexibility. Based on this we provide suggestions for development of tighter-binding CDK8 inhibitors and offer insight that can aid future computational studies.