Dickson Lab @ MSU

Targeted protein degradation is an emerging approach that utilizes cellular degradation pathways to inhibit a target protein. Small molecules such as molecular glues or PROTACs can be used to mediate the formation of a ternary complex with an E3 ligase and the target protein, which can dramatically enhance the degradation process. This approach is promising for cancer therapy, where degradation of oncogenic proteins can lead to cancer cell toxicity. To design new molecular glues, it is important to develop methods that predict how well a given molecule stabilizes a protein-protein interaction. However, conventional molecular dynamics simulations...

Neurolysin (Nln) is an M3 metallopeptidase that regulates neuropeptide concentration in the central nervous system. It has emerged as a therapeutic target for mitigating post-ischemic injury by hydrolyzing and inactivating several neuropeptides. It has been recently shown that small molecule activators, such as pyridine piperazine (Py-Pip) derivatives, can enhance Nln catalytic activity, facilitating hydrolysis of Nln substrate peptides. However, binding sites of these molecules and the mechanism of action remain unclear due to the dynamic nature of Nln. Here, we use molecular dynamics (MD) simulation of the apo and activator-bound Nln systems along with Markov state...

Peptides are desirable therapeutics due to their inherent potency, safety, cost-effectiveness and ability to engage large or more complex protein surfaces. Slower kinetics of protein-peptide (un)binding can directly influence their drug efficacy and duration of action, in part by improving plasma stability of the peptide. The CLR:RAMP1 complex and its endogenous agonist peptide CGRP are of particularly high interest because of their central role in migraine pathophysiology. A better understanding of peptide binding mechanisms is needed for the development of next-generation peptide-based drugs with optimized kinetic properties. In this study, we comparatively analyze constructs of native...

A common first step in drug design is virtual high throughput screening (VHTS), where a large number of potential drug molecules are computationally modeled in a protein binding pocket and filtered down to a smaller set of hits that can be further tested computationally or experimentally. Traditional strategies for VHTS do not account for ligand-induced conformational changes in proteins, as they typically rely on a single static structure to represent the protein. This neglects the role of binding entropy and the fact that different ligand molecules can induce slightly different conformations in the protein binding site...

Calcitonin gene-related peptide (CGRP) is a 37-amino acid neuropeptide that functions in pain signaling and neuroimmune communication. The CGRP receptor, CGRPR, is a class B GPCR that is a drug target for migraine headache and other disorders. Here, we used nanoBRET receptor binding and cAMP biosensor signaling assays and theoretical modeling to characterize the CGRPR “two-domain” peptide binding mechanism. Single-site extracellular domain (ECD)-binding and two-site ECD/transmembrane domain (TMD)-binding peptides were examined for CGRP and a high-affinity variant “ssCGRP” with modifications in the C-terminal region. Wildtype and ssCGRP(27-37) bound the ECD with affinities of 1 μM and...

Accurate prediction of molecular geometries is crucial for drug discovery and materials science. Existing fast conformer prediction algorithms often rely on approximate empirical energy functions, resulting in low accuracy. More accurate methods like ab initio molecular dynamics and Markov chain Monte Carlo can be computationally expensive due to the need for evaluating quantum mechanical energy functions. To address this, we introduce AGDIFF, a novel machine learning framework that utilizes diffusion models for efficient and accurate molecular structure prediction. AGDIFF extends previous models (such as GeoDiff) by enhancing the global, local, and edge encoders with attention mechanisms,...

The weighted ensemble (WE) algorithm is gaining popularity as a rare event method for studying long timescale processes with molecular dynamics. WE is particularly useful for determining kinetic properties, like rates of protein (un)folding and ligand (un)binding, where transition rates can be calculated from the flux of trajectories into a target basin of interest. However, this flux depends exponentially on the number of splitting events that a given trajectory experiences before reaching the target state, and can vary by orders of magnitude between WE replicates. Markov state models (MSM) are helpful tools to aggregate information across...

For many drug targets, it has been shown that the kinetics of drug binding (e.g., on rate and off rate) is more predictive of drug efficacy than thermodynamic quantities alone. This motivates the development of predictive computational models that can be used to optimize compounds on the basis of their kinetics. The structural details underpinning these computational models are found not only in the bound state but also in the short-lived ligand binding transition states. Although transition states cannot be directly observed experimentally due to their extremely short lifetimes, recent successes have demonstrated that modeling the...

Ligand design problems involve searching chemical space for a molecule with a set of desired properties. As chemical space is discrete, this search must be conducted in a pointwise manner, separately investigating one molecule at a time, which can be inefficient. We propose a method called “Flexible Topology”, where a ligand is composed of a set of shapeshifting “ghost” atoms, whose atomic identities and connectivity can dynamically change over the course of a simulation. Ghost atoms are guided toward their target positions using a translation-, rotation-, and index-invariant restraint potential. This is the first step toward...

The signaling peptides adrenomedullin 2/intermedin (AM2/IMD), adrenomedullin (AM), and CGRP have overlapping and distinct functions in the cardiovascular, lymphatic, and nervous systems by activating three shared receptors comprised of the class B GPCR CLR in complex with a RAMP1, −2, or −3 modulatory subunit. Here, we report that AM2/IMD, which is thought to be a non-selective agonist, is kinetically selective for CLR-RAMP3, known as the AM2R. AM2/IMD-AM2R elicited substantially longer duration cAMP signaling than the eight other peptide-receptor combinations due to AM2/IMD slow off-rate binding kinetics. The regions responsible for the slow off-rate were mapped to...

The prediction of (un)binding rates and free energies is of great significance to the drug design process. Although many enhanced sampling algorithms and approaches have been developed, there is not yet a reliable workflow to predict these quantities. Previously we have shown that free energies and transition rates can be calculated by directly simulating the binding and unbinding processes with our variant of the WE algorithm “Resampling of Ensembles by Variation Optimization”, or “REVO”. Here, we calculate binding free energies retrospectively for three SAMPL6 host-guest systems and prospectively for a SAMPL9 system to test a modification...

Targeted protein degradation (TPD) is a promising approach in drug discovery for degrading proteins implicated in diseases. A key step in this process is the formation of a ternary complex where a heterobifunctional molecule induces proximity of an E3 ligase to a protein of interest (POI), thus facilitating ubiquitin transfer to the POI. In this work, we characterize 3 steps in the TPD process. (1) We simulate the ternary complex formation of SMARCA2 bromodomain and VHL E3 ligase by combining hydrogen-deuterium exchange mass spectrometry with weighted ensemble molecular dynamics (MD). (2) We characterize the conformational heterogeneity...