Conformational and Dynamical Effects of Tyr32 Phosphorylation in K-Ras: Molecular Dynamics Simulation and Markov State Models Analysis

Molecular dynamics simulations for the structure-based drug design: targeting small-GTPases proteins

INTRODUCTION

Molecular Dynamics (MD) simulations can support mechanism-based drug design. Indeed, MD simulations by capturing biomolecule motions at finite temperatures can reveal hidden binding sites, accurately predict drug-binding poses, and estimate the thermodynamics and kinetics, crucial information for drug discovery campaigns. Small-Guanosine Triphosphate Phosphohydrolases (GTPases) regulate a cascade of signaling events, that affect most cellular processes. Their deregulation is linked to several diseases, making them appealing drug targets. The broad roles of small-GTPases in cellular processes and the recent approval of a covalent KRas inhibitor as an anticancer agent renewed the interest in targeting small-GTPase with small molecules.

AREA COVERED

This review emphasizes the role of MD simulations in elucidating small-GTPase mechanisms, assessing the impact of cancer-related variants, and discovering novel inhibitors.

EXPERT OPINION

The application of MD simulations to small-GTPases exemplifies the role of MD simulations in the structure-based drug design process for challenging biomolecular targets. Furthermore, AI and machine learning-enhanced MD simulations, coupled with the upcoming power of quantum computing, are promising instruments to target elusive small-GTPases mutations and splice variants. This powerful synergy will aid in developing innovative therapeutic strategies associated to small-GTPases deregulation, which could potentially be used for personalized therapies and in a tissue-agnostic manner to treat tumors with mutations in small-GTPases.

Investigating the effects of cysteine-118 oxidation on G12D KRas structure and dynamics: insights from MD simulations

Mutations of Ras proteins are believed to be among the most prominent causes of cancer. There is increasing evidence that the activity of Ras may be controlled by the redox state of cysteine residues located within the NKCD motif. This redox signaling is critical to both physiological and pathological processes and occurs when C118 is oxidized in a reversible manner. In this study, we used atomistic molecular dynamics simulations and Markov state models to investigate the structural and conformational effects of C118 oxidation on the oncogenic mutant KRas(G12D). While both mutants share common features and exhibit some distinct conformational states and fluctuations, we have found that the oxidized variant KRas(G12D/C118SOH) is more dynamic than the unoxidized counterpart, particularly in the switch II region. Additionally, C118 oxidation is found to alter the structure of the nucleotide-binding site and the switch regions as well as perturb the conformational equilibrium between Ras active and inactive states. These conformational preferences may alter the affinity to different effectors, resulting in selective downstream activation. Our results are anticipated to help future drug development efforts aimed at KRAS-related anticancer treatment.Communicated by Ramaswamy H. Sarma.

Engineered β-glycosidase from Hyperthermophilic Sulfolobus solfataricus with Improved Rd-hydrolyzing Activity for Ginsenoside Compound K Production

Hyperthermophilic Sulfolobus solfataricus β-glycosidase (SS-βGly), with higher stability and activity than mesophilic enzymes, has potential for industrial ginsenosides biotransformation. However, its relatively low ginsenoside Rd-hydrolyzing activity limits the production of pharmaceutically active minor ginsenoside compound K (CK). In this study, first, we used molecular docking to predict the key enzyme residues that may hypothetically interact with ginsenoside Rd. Then, based on sequence alignment and alanine scanning mutagenesis approach, key variant sites were identified that might improve the enzyme catalytic efficiency. The enzyme catalytic efficiency (kcat/Km) and substrate affinity (Km) of the N264D variant enzyme for ginsenoside Rd increased by 60% and decreased by 17.9% compared with WT enzyme, respectively, which may be due to a decrease in the binding free energy (∆G) between the variant enzyme and substrate Rd. In addition, Markov state models (MSM) analysis during the whole 1000-ns MD simulations indicated that altering N264 to D made the variant enzyme achieve a more stable SS-βGly conformational state than the wild-type (WT) enzyme and corresponding Rd complex. Under identical conditions, the relative activities and the CK conversion rates of the N264D enzyme were 1.7 and 1.9 folds higher than those of the WT enzyme. This study identified an excellent hyperthermophilic β-glycosidase candidate for industrial biotransformation of ginsenosides.

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning

The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg2+ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS.

sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data

Class-switch recombination (CSR) is an integral part of B cell maturation. Here we present sciCSR (pronounced 'scissor', single-cell inference of class-switch recombination), a computational pipeline that analyzes CSR events and dynamics of B cells from single-cell RNA sequencing (scRNA-seq) experiments. Validated on both simulated and real data, sciCSR re-analyzes scRNA-seq alignments to differentiate productive heavy-chain immunoglobulin transcripts from germline 'sterile' transcripts. From a snapshot of B cell scRNA-seq data, a Markov state model is built to infer the dynamics and direction of CSR. Applying sciCSR on severe acute respiratory syndrome coronavirus 2 vaccination time-course scRNA-seq data, we observe that sciCSR predicts, using data from an earlier time point in the collected time-course, the isotype distribution of B cell receptor repertoires of subsequent time points with high accuracy (cosine similarity ~0.9). Using processes specific to B cells, sciCSR identifies transitions that are often missed by conventional RNA velocity analyses and can reveal insights into the dynamics of B cell CSR during immune response.

The switch states of the GDP-bound HRAS affected by point mutations: a study from Gaussian accelerated molecular dynamics simulations and free energy landscapes

Point mutations play a vital role in the conformational transformation of HRAS. In this work, Gaussian accelerated molecular dynamics (GaMD) simulations followed by constructions of free energy landscapes (FELs) were adopted to explore the effect of mutations D33K, A59T and L120A on conformation states of the GDP-bound HRAS. The results from the post-processing analyses on GaMD trajectories suggest that mutations alter the flexibility and motion modes of the switch domains from HRAS. The analyses from FELs show that mutations induce more disordered states of the switch domains and affect interactions of GDP with HRAS, implying that mutations yield a vital effect on the binding of HRAS to effectors. The GDP-residue interaction network revealed by our current work indicates that salt bridges and hydrogen bonding interactions (HBIs) play key roles in the binding of GDP to HRAS. Furthermore, instability in the interactions of magnesium ions and GDP with the switch SI leads to the extreme disorder of the switch domains. This study is expected to provide the energetic basis and molecular mechanism for further understanding the function of HRAS.Communicated by Ramaswamy H. Sarma.

Tutorial on how to build non-Markovian dynamic models from molecular dynamics simulations for studying protein conformational changes

Protein conformational changes play crucial roles in their biological functions. In recent years, the Markov State Model (MSM) constructed from extensive Molecular Dynamics (MD) simulations has emerged as a powerful tool for modeling complex protein conformational changes. In MSMs, dynamics are modeled as a sequence of Markovian transitions among metastable conformational states at discrete time intervals (called lag time). A major challenge for MSMs is that the lag time must be long enough to allow transitions among states to become memoryless (or Markovian). However, this lag time is constrained by the length of individual MD simulations available to track these transitions. To address this challenge, we have recently developed Generalized Master Equation (GME)-based approaches, encoding non-Markovian dynamics using a time-dependent memory kernel. In this Tutorial, we introduce the theory behind two recently developed GME-based non-Markovian dynamic models: the quasi-Markov State Model (qMSM) and the Integrative Generalized Master Equation (IGME). We subsequently outline the procedures for constructing these models and provide a step-by-step tutorial on applying qMSM and IGME to study two peptide systems: alanine dipeptide and villin headpiece. This Tutorial is available at https://github.com/xuhuihuang/GME_tutorials. The protocols detailed in this Tutorial aim to be accessible for non-experts interested in studying the biomolecular dynamics using these non-Markovian dynamic models.

Unraveling the Significance of Mg2+ Dependency and Nucleotide Binding Specificity of H-RAS

RAS is a small GTPase and acts as a binary molecular switch; the transition from its active to inactive state plays a crucial role in various cell signaling processes. Molecular dynamics simulations at the atomistic level suggest that the absence of cofactor Mg2+ ion generally leads to pronounced structural changes in the Switch-I than Switch-II regions and assists GTP binding. The presence of the Mg2+ ion also restricts the rotation of ϒ phosphate and enhances the hydrolysis rate of GTP. Further, the simulations reveal that the stability of the protein is almost uncompromised when Mg2+ is replaced with Zn2+ and not the Ca2+ ion. The specificity of H-RAS to GTP was evaluated by substituting with ATP and CTP, which indicates that the binding pocket tolerates purine bases over pyrimidine bases. However, the D119 residue specifically interacts with the guanine base and serves as one of the primary interactions that leads to the selectivity of GTP over ATP. The ring displacement of 32Y serves as gate dynamics in H-RAS which are important for its interaction with GAP for the nucleotide exchange and is restricted in the presence of ATP. Finally, the point mutations 61, 16, and 32 influence the structural changes, specifically in the Switch-II region, which are expected to impact the GTP hydrolysis and thus are termed oncogenic mutations.

Unveiling the State Transition Mechanisms of Ras Proteins through Enhanced Sampling and QM/MM Simulations

In cells, wild-type RasGTP complexes exist in two distinct states: active State 2 and inactive State 1. These complexes regulate their functions by transitioning between the two states. However, the mechanisms underlying this state transition have not been clearly elucidated. To address this, we conducted a detailed simulation study to characterize the energetics of the stable states involved in the state transitions of the HRasGTP complex, specifically from State 2 to State 1. This was achieved by employing multiscale quantum mechanics/molecular mechanics and enhanced sampling molecular dynamics methods. Based on the simulation results, we constructed the two-dimensional free energy landscapes that provide crucial information about the conformational changes of the HRasGTP complex from State 2 to State 1. Furthermore, we also explored the conformational changes from the intermediate state to the product state during guanosine triphosphate hydrolysis. This study on the conformational changes involved in the HRas state transitions serves as a valuable reference for understanding the corresponding events of both KRas and NRas as well.

Far-reaching effects of tyrosine64 phosphorylation on Ras revealed with BeF3- complexes

Tyrosine phosphorylation on Ras by Src kinase is known to uncouple Ras from upstream regulation and downstream communication. However, the mechanisms by which phosphorylation modulates these interactions have not been detailed. Here, the major mono-phosphorylation level on tyrosine64 is quantified by 31P NMR and mutagenesis. Crystal structures of unphosphorylated and tyrosine64-phosphorylated Ras in complex with a BeF3- ground state analogue reveal "closed" Ras conformations very different from those of the "open" conformations previously observed for non-hydrolysable GTP analogue structures of Ras. They deliver new mechanistic and conformational insights into intrinsic GTP hydrolysis. Phosphorylation of tyrosine64 delivers conformational changes distant from the active site, showing why phosphorylated Ras has reduced affinity to its downstream effector Raf. 19F NMR provides evidence for changes in the intrinsic GTPase and nucleotide exchange rate and identifies the concurrent presence of a major "closed" conformation alongside a minor yet functionally important "open" conformation at the ground state of Ras. This study expands the application of metal fluoride complexes in revealing major and minor conformational changes of dynamic and modified Ras proteins.

GTP-Bound N-Ras Conformational States and Substates Are Modulated by Membrane and Point Mutation

Oncogenic Ras proteins are known to present multiple conformational states, as reported by the great variety of crystallographic structures. The GTP-bound states are grouped into two main states: the "inactive" state 1 and the "active" state 2. Recent reports on H-Ras have shown that state 2 exhibits two substates, directly related to the orientation of Tyr32: toward the GTP-bound pocket and outwards. In this paper, we show that N-Ras exhibits another substate of state 2, related to a third orientation of Tyr32, toward Ala18 and parallel to the GTP-bound pocket. We also show that this substate is highly sampled in the G12V mutation of N-Ras and barely present in its wild-type form, and that the G12V mutation prohibits the sampling of the GTPase-activating protein (GAP) binding substate, rendering this mutation oncogenic. Furthermore, using molecular dynamics simulations, we explore the importance of the membrane on N-Ras' conformational state dynamics and its strong influence on Ras protein stability. Moreover, the membrane has a significant influence on the conformational (sub)states sampling of Ras. This, in turn, is of crucial importance in the activation/deactivation cycle of Ras, due to the binding of guanine nucleotide exchange factor proteins (GEFs)/GTPase-activating proteins (GAPs).

In silico design of a lipid-like compound targeting KRAS4B-G12D through non-covalent bonds

One of the most common drivers in human cancer is the peripheral membrane protein KRAS4B, able to promote oncogenic signalling. To signal, oncogenic KRAS4B not only requires a sufficient nucleotide exchange, but also needs to recruit effectors by exposing its effector-binding sites while anchoring to the phospholipid bilayer where KRAS4B-mediated signalling events occur. The enzyme phosphodiesterase-δ plays an important role in sequestering KRAS4B from the cytoplasm and targeting it to cellular membranes of different cell species. In this work, we present an in silico design of a lipid-like compound that has the remarkable feature of being able to target both an oncogenic KRAS4B-G12D mutant and the phosphodiesterase-δ enzyme. This double action is accomplished by adding a lipid tail (analogous to the farnesyl group of the KRAS4B protein) to an previously known active compound (2H-1,2,4-benzothiadiazine, 3,4-dihydro-,1,1-dioxide). The proposed lipid-like molecule was found to lock KRAS4B-G12D in its GDP-bound state by adjusting the effector-binding domain to be blocked by the interface of the lipid bilayer. Meanwhile, it can tune GTP-bound KRAS4B-G12D to shift from the active orientation state to the inactive state. The proposed compound is also observed to stably accommodate itself in the prenyl-binding pocket of phosphodiesterase-δ, which impairs KRAS4B enrichment at the lipid bilayer, potentially reducing the proliferation of KRAS4B inside the cytoplasm and its anchoring at the bilayer. In conclusion, we report a potential inhibitor of KRAS4B-G12D with a lipid tail attached to a specific warhead, a compound which has not yet been considered for drugs targeting RAS mutants. Our work provides new ways to target KRAS4B-G12D and can also foster drug discovery efforts for the targeting of oncogenes of the RAS family and beyond.

Virtual screening and biological activity evaluation of novel efflux pump inhibitors targeting AdeB

The AdeABC efflux pump is an important mechanism causing multidrug resistance in Acinetobacter baumannii, and its main component AdeB can recognize carbapenems, aminoglycosides, and other multi-class antibiotics and efflux them intracellularly, which is an ideal target for the development of anti-multidrug resistant bacteria drugs. Here, we combined multiple computer-aided drug design methods to target AdeB to identify promising novel structural inhibitors. Virtual screening was performed by molecular docking and molecular dynamics simulation (MD) and 12 potential compounds were identified from the databases. Meanwhile, their biological activities were validated by in vitro activity assays, and ChemDiv L676-2179 (γ-IFN), ChemDiv L676-1461, and Chembridge 53717615 were confirmed to suppress efflux effects and restore antibiotic susceptibility of resistant bacteria, which are expected to be developed as adjuvant drugs for the treatment of multi-drug resistant Acinetobacter baumannii clinical infections.

Uncertainties in Markov State Models of Small Proteins

Markov state models are widely used to describe and analyze protein dynamics based on molecular dynamics simulations, specifically to extract functionally relevant characteristic time scales and motions. Particularly for larger biomolecules such as proteins, however, insufficient sampling is a notorious concern and often the source of large uncertainties that are difficult to quantify. Furthermore, there are several other sources of uncertainty, such as choice of the number of Markov states and lag time, choice and parameters of dimension reduction preprocessing step, and uncertainty due to the limited number of observed transitions; the latter is often estimated via a Bayesian approach. Here, we quantified and ranked all of these uncertainties for four small globular test proteins. We found that the largest uncertainty is due to insufficient sampling and initially increases with the total trajectory length T up to a critical tipping point, after which it decreases as 1 / T , thus providing guidelines for how much sampling is required for given accuracy. We also found that single long trajectories yielded better sampling accuracy than many shorter trajectories starting from the same structure. In comparison, the remaining sources of the above uncertainties are generally smaller by a factor of about 5, rendering them less of a concern but certainly not negligible. Importantly, the Bayes uncertainty, commonly used as the only uncertainty estimate, captures only a relatively small part of the true uncertainty, which is thus often drastically underestimated.

An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes

Conformational changes (i.e., dynamic transitions between pairs of conformational states) play important roles in many chemical and biological processes. Constructing the Markov state model (MSM) from extensive molecular dynamics (MD) simulations is an effective approach to dissect the mechanism of conformational changes. When combined with transition path theory (TPT), MSM can be applied to elucidate the ensemble of kinetic pathways connecting pairs of conformational states. However, the application of TPT to analyze complex conformational changes often results in a vast number of kinetic pathways with comparable fluxes. This obstacle is particularly pronounced in heterogeneous self-assembly and aggregation processes. The large number of kinetic pathways makes it challenging to comprehend the molecular mechanisms underlying conformational changes of interest. To address this challenge, we have developed a path classification algorithm named latent-space path clustering (LPC) that efficiently lumps parallel kinetic pathways into distinct metastable path channels, making them easier to comprehend. In our algorithm, MD conformations are first projected onto a low-dimensional space containing a small set of collective variables (CVs) by time-structure-based independent component analysis (tICA) with kinetic mapping. Then, MSM and TPT are constructed to obtain the ensemble of pathways, and a deep learning architecture named the variational autoencoder (VAE) is used to learn the spatial distributions of kinetic pathways in the continuous CV space. Based on the trained VAE model, the TPT-generated ensemble of kinetic pathways can be embedded into a latent space, where the classification becomes clear. We show that LPC can efficiently and accurately identify the metastable path channels in three systems: a 2D potential, the aggregation of two hydrophobic particles in water, and the folding of the Fip35 WW domain. Using the 2D potential, we further demonstrate that our LPC algorithm outperforms the previous path-lumping algorithms by making substantially fewer incorrect assignments of individual pathways to four path channels. We expect that LPC can be widely applied to identify the dominant kinetic pathways underlying complex conformational changes.

Memory Unlocks the Future of Biomolecular Dynamics: Transformative Tools to Uncover Physical Insights Accurately and Efficiently

Conformational changes underpin function and encode complex biomolecular mechanisms. Gaining atomic-level detail of how such changes occur has the potential to reveal these mechanisms and is of critical importance in identifying drug targets, facilitating rational drug design, and enabling bioengineering applications. While the past two decades have brought Markov state model techniques to the point where practitioners can regularly use them to glimpse the long-time dynamics of slow conformations in complex systems, many systems are still beyond their reach. In this Perspective, we discuss how including memory (i.e., non-Markovian effects) can reduce the computational cost to predict the long-time dynamics in these complex systems by orders of magnitude and with greater accuracy and resolution than state-of-the-art Markov state models. We illustrate how memory lies at the heart of successful and promising techniques, ranging from the Fokker-Planck and generalized Langevin equations to deep-learning recurrent neural networks and generalized master equations. We delineate how these techniques work, identify insights that they can offer in biomolecular systems, and discuss their advantages and disadvantages in practical settings. We show how generalized master equations can enable the investigation of, for example, the gate-opening process in RNA polymerase II and demonstrate how our recent advances tame the deleterious influence of statistical underconvergence of the molecular dynamics simulations used to parameterize these techniques. This represents a significant leap forward that will enable our memory-based techniques to interrogate systems that are currently beyond the reach of even the best Markov state models. We conclude by discussing some current challenges and future prospects for how exploiting memory will open the door to many exciting opportunities.

Effect of phosphorylation on the structural dynamics, thermal stability of human dopamine transporter: A simulation study using normal modes, molecular dynamics and Markov State Model

The Human Dopamine Transporter (hDAT) plays an essential role in modulating the Influx/Efflux of dopamine, and it is involved in the mechanism of certain neurodegenerative diseases such as Parkinson's disease. Several studies have reported important states for Dopamine transport: outward-facing open state (OFo), the outward-facing closed state (OFc), the holo-occluded state closed (holo), and the inward-facing open state (IFo). Furthermore, experimental assays have shown that different phosphorylation conditions in hDAT can affect the rate of dopamine absorption. We present a protocol using hybrid simulation methods to study the conformational dynamics and stability of states of hDAT under different phosphorylation sites. With this protocol, we explored the conformational space of hDAT, identified the states, and evaluated the free energy differences and the transition probabilities between them in each of the phosphorylation cases. We also presented the conformational changes and correlated them with those described in the literature. There is a thesis/hypothesis that the phosphorylation condition corresponding to NP-333 system (where all sites Ser/Thr from residue 2 to 62 and 254 to 613 are phosphorylated, except residue 333) would decrease the rate of dopamine transport from the extracellular medium to the intracellular medium by hDAT as previously described in the literature by Lin et al., 2003. Our results corroborated this thesis/hypothesis and the data reported. It is probably due to the affectation/changes/alteration of the conformational dynamics of this system that makes the intermediate states more likely and makes it difficult to initial states associated with the uptake of dopamine in the extracellular medium, corroborating the experimental results. Furthermore, our results showed that just single phosphorylation/dephosphorylation could alter intrinsic protein motions affecting the sampling of one or more states necessary for dopamine transport. In this sense, the modification of phosphorylation influences protein movements and conformational preferences, affecting the stability of states and the transition between them and, therefore, the transport.

Deciphering Conformational Changes of the GDP-Bound NRAS Induced by Mutations G13D, Q61R, and C118S through Gaussian Accelerated Molecular Dynamic Simulations

The conformational changes in switch domains significantly affect the activity of NRAS. Gaussian-accelerated molecular dynamics (GaMD) simulations of three separate replicas were performed to decipher the effects of G13D, Q16R, and C118S on the conformational transformation of the GDP-bound NRAS. The analyses of root-mean-square fluctuations and dynamics cross-correlation maps indicated that the structural flexibility and motion modes of the switch domains involved in the binding of NRAS to effectors are highly altered by the G13D, Q61R, and C118Smutations. The free energy landscapes (FELs) suggested that mutations induce more energetic states in NRAS than the GDP-bound WT NRAS and lead to high disorder in the switch domains. The FELs also indicated that the different numbers of sodium ions entering the GDP binding regions compensate for the changes in electrostatic environments caused by mutations, especially for G13D. The GDP–residue interactions revealed that the disorder in the switch domains was attributable to the unstable hydrogen bonds between GDP and two residues, V29 and D30. This work is expected to provide information on the energetic basis and dynamics of conformational changes in switch domains that can aid in deeply understanding the target roles of NRAS in anticancer treatment.

Markov State Models and Molecular Dynamics Simulations Reveal the Conformational Transition of the Intrinsically Disordered Hypervariable Region of K-Ras4B to the Ordered Conformation

K-Ras4B, the most frequently mutated Ras isoform in human tumors, plays a vital part in cell growth, differentiation, and survival. Its tail, the C-terminal hypervariable region (HVR), is involved in anchoring K-Ras4B at the cellular plasma membrane and in isoform-specific protein-protein interactions and signaling. In the inactive guanosine diphosphate-bound state, the intrinsically disordered HVR interacts with the catalytic domain at the effector-binding region, rendering K-Ras4B in its autoinhibited state. Activation releases the HVR from the catalytic domain, with its ensemble favoring an ordered α-helical structure. The large-scale conformational transition of the HVR from the intrinsically disordered to the ordered conformation remains poorly understood. Here, we deploy a computational scheme that integrates a transition path-generation algorithm, extensive molecular dynamics simulation, and Markov state model analysis to investigate the conformational landscape of the HVR transition pathway. Our findings reveal a stepwise pathway for the HVR transition and uncover several key conformational substates along the transition pathway. Importantly, key interactions between the HVR and the catalytic domain are unraveled, highlighting the pathogenesis of K-Ras4B mild mutations in several congenital developmental anomaly syndromes. Together, these findings provide a deeper understanding of the HVR transition mechanism and the regulation of K-Ras4B activity at an atomic level.

TRPM8-Rap1A Interaction Sites as Critical Determinants for Adhesion and Migration of Prostate and Other Epithelial Cancer Cells

Emerging evidence indicates that the TRPM8 channel plays an important role in prostate cancer (PCa) progression, by impairing the motility of these cancer cells. Here, we reveal a novel facet of PCa motility control via direct protein-protein interaction (PPI) of the channel with the small GTPase Rap1A. The functional interaction of the two proteins was assessed by active Rap1 pull-down assays and live-cell imaging experiments. Molecular modeling analysis allowed the identification of four putative residues involved in TRPM8-Rap1A interaction. Point mutations of these sites impaired PPI as shown by GST-pull-down, co-immunoprecipitation, and PLA experiments and revealed their key functional role in the adhesion and migration of PC3 prostate cancer cells. More precisely, TRPM8 inhibits cell migration and adhesion by trapping Rap1A in its GDP-bound inactive form, thus preventing its activation at the plasma membrane. In particular, residues E207 and Y240 in the sequence of TRPM8 and Y32 in that of Rap1A are critical for the interaction between the two proteins not only in PC3 cells but also in cervical (HeLa) and breast (MCF-7) cancer cells. This study deepens our knowledge of the mechanism through which TRPM8 would exert a protective role in cancer progression and provides new insights into the possible use of TRPM8 as a new therapeutic target in cancer treatment.

Identification of functional substates of KRas during GTP hydrolysis with enhanced sampling simulations

As the hub of major signaling pathways, Ras proteins are implicated in 19% of tumor-caused cancers due to perturbations in their conformational and/or catalytic properties. Despite numerous studies, the functions of the conformational substates for the most important isoform, KRas, remain elusive. In this work, we perform an extensive simulation analysis on the conformational landscape of KRas in its various chemical states during the GTP hydrolysis cycle: the reactant state KRasGTP·Mg²⁺, the intermediate state KRasGDP·Pi·Mg²⁺ and the product state KRasGDP·Mg²⁺. The results from enhanced sampling simulations reveal that State 1 of KRasGTP·Mg²⁺ has multiple stable substates in solution, one of which might account for interacting with GEFs. State 2 of KRasGTP·Mg²⁺ features two substates "Tyr32_in" and "Tyr32_out", which are poised to interact with effectors and GAPs, respectively. For the intermediate state KRasGDP·Pi·Mg²⁺, Gln61 and Pi are found to assume a broad set of conformations, which might account for the weak oncogenic effect of Gln61 mutations in KRas in contrast to the situation in HRas and NRas. Finally, the product state KRasGDP·Mg²⁺ has more than two stable substates in solution, pointing to a conformation-selection mechanism for complexation with GEFs. Based on these results, some specific inhibition strategies for targeting the binding sites of the high-energy substates of KRas during GTP hydrolysis are discussed.

Q61 mutant-mediated dynamics changes of the GTP-KRAS complex probed by Gaussian accelerated molecular dynamics and free energy landscapes

Understanding the molecular mechanism of the GTP-KRAS binding is significant for improving the target roles of KRAS in cancer treatment. In this work, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations were applied to decode the effect of Q61A, Q61H and Q61L on the activity of KRAS. Dynamics analyses based on MR-GaMD trajectory reveal that motion modes and dynamics behavior of the switch domain in KRAS are heavily affected by the three Q61 mutants. Information of free energy landscapes (FELs) shows that Q61A, Q61H and Q61L induce structural disorder of the switch domain and disturb the activity of KRAS. Analysis of the interaction network uncovers that the decrease in the stability of hydrogen bonding interactions (HBIs) of GTP with residues V29 and D30 induced by Q61A, Q61H and Q61L is responsible for the structural disorder of the switch-I and that in the occupancy of the hydrogen bond between GTP and residue G60 leads to the structural disorder of the switch-II. Thus, the high disorder of the switch domain caused by three current Q61 mutants produces a significant effect on binding of KRAS to its effectors. This work is expected to provide useful information for further understanding function and target roles of KRAS in anti-cancer drug development.

The Q61H mutation decouples KRAS from upstream regulation and renders cancer cells resistant to SHP2 inhibitors

Cancer cells bearing distinct KRAS mutations exhibit variable sensitivity to SHP2 inhibitors (SHP2i). Here we show that cells harboring KRAS Q61H are uniquely resistant to SHP2i, and investigate the underlying mechanisms using biophysics, molecular dynamics, and cell-based approaches. Q61H mutation impairs intrinsic and GAP-mediated GTP hydrolysis, and impedes activation by SOS1, but does not alter tyrosyl phosphorylation. Wild-type and Q61H-mutant KRAS are both phosphorylated by Src on Tyr32 and Tyr64 and dephosphorylated by SHP2, however, SHP2i does not reduce ERK phosphorylation in KRAS Q61H cells. Phosphorylation of wild-type and Gly12-mutant KRAS, which are associated with sensitivity to SHP2i, confers resistance to regulation by GAP and GEF activities and impairs binding to RAF, whereas the near-complete GAP/GEF-resistance of KRAS Q61H remains unaltered, and high-affinity RAF interaction is retained. SHP2 can stimulate KRAS signaling by modulating GEF/GAP activities and dephosphorylating KRAS, processes that fail to regulate signaling of the Q61H mutant.

SHP2 promotes RAS-driven MAPK signalling, but it is unclear why cancer cells with distinct KRAS mutations exhibit differential sensitivity to SHP2 inhibition. Here the authors show that KRAS Q61H is decoupled from SHP2- mediated upstream regulation, thus Q61H pancreatic cancer cells maintain MAPK signalling and are refractory to SHP2 inhibitors.

Targeting RAS phosphorylation in cancer therapy: Mechanisms and modulators

RAS, a member of the small GTPase family, functions as a binary switch by shifting between inactive GDP-loaded and active GTP-loaded state. RAS gain-of-function mutations are one of the leading causes in human oncogenesis, accounting for ∼19% of the global cancer burden. As a well-recognized target in malignancy, RAS has been intensively studied in the past decades. Despite the sustained efforts, many failures occurred in the earlier exploration and resulted in an ‘undruggable’ feature of RAS proteins. Phosphorylation at several residues has been recently determined as regulators for wild-type and mutated RAS proteins. Therefore, the development of RAS inhibitors directly targeting the RAS mutants or towards upstream regulatory kinases supplies a novel direction for tackling the anti-RAS difficulties. A better understanding of RAS phosphorylation can contribute to future therapeutic strategies. In this review, we comprehensively summarized the current advances in RAS phosphorylation and provided mechanistic insights into the signaling transduction of associated pathways. Importantly, the preclinical and clinical success in developing anti-RAS drugs targeting the upstream kinases and potential directions of harnessing allostery to target RAS phosphorylation sites were also discussed.

Computational investigation to identify potent inhibitors of the GTPase-Kirsten RAt sarcoma virus (K-Ras) mutants G12C and G12D

K-Ras mutations are frequent in various cancer types, and according to recent research, K-Ras possesses four-drug targeting sites. This increased our interest in finding potential small molecule inhibitors with anticancer activity to treat K-Ras-driven cancers. We utilized integrated bioinformatic strategies, such as XP docking, MM-GBSA, cell-line cytotoxicity prediction, ADMET, and molecular simulation, to discover potential inhibitors of G12C and G12D mutants compared to sotorasib, which is a recent FDA-approved inhibitor of G12C. We identified compounds, such as flupentixol, amlodipine, and fluvoxamine, for the G12C mutant and paroxetine, flupentixol, and zuclopenthixol for the G12D mutant with significant inhibitory functions. All five compounds bound to the H95 cryptic groove of mutant K-Ras with high efficiency and, like sotorasib, retained a novel binding mechanism with additional hydrophobic interactions at the molecular level. Furthermore, the simulation studies suggested that the binding of flupentixol and amlodipine to G12C stabilizes switch I and switch II. In contrast, paroxetine and flupentixol to G12D showed a similar trend compared to sotorasib complexes. Thus, despite the very dynamic functionality of K-Ras switches I and II, the binding of shortlisted compounds is highly stable. Therefore, the reported study provides potential drug candidates for K-Ras inhibition that can be further developed with in vitro and in vivo evidence for targeted therapy.

Conformational transformation of switch domains in GDP/K-Ras induced by G13 mutants: An investigation through Gaussian accelerated molecular dynamics simulations and principal component analysis

Mutations in K-Ras are involved in a large number of all human cancers, thus, K-Ras is regarded as a promising target for anticancer drug design. Understanding the target roles of K-Ras is important for providing insights on the molecular mechanism underlying the conformational transformation of the switch domains in K-Ras due to mutations. In this study, multiple replica Gaussian accelerated molecular (MR-GaMD) simulations and principal component analysis (PCA) were applied to probe the effect of G13A, G13D and G13I mutations on conformational transformations of the switch domains in GDP-associated K-Ras. The results suggest that G13A, G13D and G13I enhance the structural flexibility of the switch domains, change the correlated motion modes of the switch domains and strengthen the total motion strength of K-Ras compared with the wild-type (WT) K-Ras. Free energy landscape analyses not only show that the switch domains of the GDP-bound inactive K-Ras mainly exist as a closed state but also indicate that mutations evidently alter the free energy profile of K-Ras and affect the conformational transformation of the switch domains between the closed and open states. Analyses of hydrophobic interaction contacts and hydrogen bonding interactions show that the mutations scarcely change the interaction network of GDP with K-Ras and only disturb the interaction of GDP with the switch (SW1). In summary, two newly introduced mutations, G13A and G13I, play similar adjustment roles in the conformational transformations of two switch domains to G13D and are possibly utilized to tune the activity of K-Ras and the binding of guanine nucleotide exchange factors.

Mutation-Induced Impacts on the Switch Transformations of the GDP- and GTP-Bound K-Ras: Insights from Multiple Replica Gaussian Accelerated Molecular Dynamics and Free Energy Analysis

Mutations yield significant effect on the structural flexibility of two switch domains, SW1 and SW2, in K-Ras, which is considered as an important target of anticancer drug design. To unveil a molecular mechanism with regard to mutation-mediated tuning on the activity of K-Ras, multiple replica Gaussian accelerated molecular dynamics (MR-GaMD) simulations followed by analysis of free energy landscapes (FELs) are performed on the GDP- and GTP-bound wild-type (WT), G12V, and D33E K-Ras. The results suggest that G12V and D33E not only evidently change the flexibility of SW1 and SW2 but also greatly affect correlated motions of SW1 and SW2 separately relative to the P-loop and SW1, which exerts a certain tuning on the activity of K-Ras. The information stemming from the analyses of FELs reveals that the conformations of SW1 and SW2 are in high disorders in the GDP- and GTP-associated WT and mutated K-Ras, possibly producing significant effect on binding of guanine nucleotide exchange factors or effectors to K-Ras. The interaction networks of GDP and GTP with K-Ras are identified and the results uncover that the instability in hydrogen-bonding interactions of SW1 with GDP and GTP is mostly responsible for conformational disorder of SW1 and SW2 as well as tunes the activity of oncogenic K-Ras.

Active and Inactive Cdc42 Differ in Their Insert Region Conformational Dynamics

Cell division control protein 42 homolog (Cdc42) protein, a Ras superfamily GTPase, regulates cellular activities, including cancer progression. Using all-atom molecular dynamics (MD) simulations and essential dynamic analysis, we investigated the structure and dynamics of the catalytic domains of GDP-bound (inactive) and GTP-bound (active) Cdc42 in solution. We discovered substantial differences in the dynamics of the inactive and active forms, particularly in the "insert region" (residues 122-135), which plays a role in Cdc42 activation and binding to effectors. The insert region has larger conformational flexibility in the GDP-bound Cdc42 than in the GTP-bound Cdc42. The G2 loop and switch I at the effector lobe of the catalytic domain exhibit large conformational changes in both the GDP- and the GTP-bound systems, but in the GTP-bound Cdc42, the switch I interactions with GTP are retained. Oncogenic mutations were identified in the Ras superfamily. In Cdc42, the G12V and Q61L mutations decrease the GTPase activity. We simulated these mutations in both GDP- and GTP-bound Cdc42. Although the overall structural organization is quite similar between the wild type and the mutants, there are small differences in the conformational dynamics, especially in the two switch regions. Taken together, the G12V and Q61L mutations may play a role similar to their K-Ras counterparts in nucleotide binding and activation. The conformational differences, which are mainly in the insert region and, to a lesser extent, in the switch regions flanking the nucleotide binding site, can shed light on binding and activation. We propose that the differences are due to a network of hydrogen bonds that gets disrupted when Cdc42 is bound to GDP, a disruption that does not exist in other Rho GTPases. The differences in the dynamics between the two Cdc42 states suggest that the inactive conformation has reduced ability to bind to effectors.

Exploring the folding process of human βB2-crystallin using multiscale molecular dynamics and the Markov state model

Adequate knowledge of protein conformations is crucial for understanding their function and their association properties with other proteins. The cataract disease is correlated with conformational changes in key proteins called crystallins. These changes are due to mutations or post-translational modifications that may lead to protein unfolding, and thus the formation of aggregate states. Human βB2-crystallin (HβB2C) is found in high proportion in the eye lens, and its mutations are related to some cataracts. HβB2C also associates into dimers, tetramers, and other higher-order supramolecular complexes. However, it is the only protein of the βγ-crystallin family that has been found in an extended conformation. Therefore, we hypothesize that the extended conformation is not energetically favourable and that HβB2C may adopt a closed (completely folded) conformation, similar to the other members of the βγ-crystallin family. To corroborate this hypothesis, we performed extensive molecular dynamics simulations of HβB2C in its monomeric and dimeric conformations, using all-atom and coarse-grained scales. We employed Markov state model (MSM) analysis to characterize the conformational and kinetically relevant states in the folding process of monomeric HβB2C. The MSM analysis clearly shows that HβB2C adopts a completely folded structure, and this conformation is the most kinetically and energetically favourable one. In contrast, the extended conformations are kinetically unstable and energetically unfavourable. Our MSM analysis also reveals a key metastable state, which is particularly interesting because it is from this state that the folded state is reached. The folded state is stabilized by the formation of two salt bridges between the residue-pairs E74-R187 and R97-E166 and the two hydrophobic residue-pairs V59-L164 and V72-V151. Furthermore, free energy surface (FES) analysis revealed that the HβB2C dimer with both monomers in a closed conformation (face-en-face dimer) is energetically more stable than the domain-swapped dimer (crystallographic structure). The results presented in this report shed light on the molecular details of the folding mechanism of HβB2C in an aqueous environment and may contribute to interpreting different experimental findings. Finally, a detailed knowledge of HβB2C folding may be key to the rational design of potential molecules to treat cataract disease.

How to make an undruggable enzyme druggable: lessons from ras proteins

Significant advances have been made toward discovering allosteric inhibitors for challenging drug targets such as the Ras family of membrane-associated signaling proteins. Malfunction of Ras proteins due to somatic mutations is associated with up to a quarter of all human cancers. Computational techniques have played critical roles in identifying and characterizing allosteric ligand-binding sites on these proteins, and to screen ligand libraries against those sites. These efforts, combined with a wide range of biophysical, structural, biochemical and cell biological experiments, are beginning to yield promising inhibitors to treat malignancies associated with mutated Ras proteins. In this chapter, we discuss some of these developments and how the lessons learned from Ras might be applied to similar other challenging drug targets.