Dynamically-Driven Inactivation of the Catalytic Machinery of the SARS 3C-Like Protease by the N214A Mutation on the Extra Domain

Despite utilizing the same chymotrypsin fold to host the catalytic machinery, coronavirus 3C-like proteases (3CLpro) noticeably differ from picornavirus 3C proteases in acquiring an extra helical domain in evolution. Previously, the extra domain was demonstrated to regulate the catalysis of the SARS-CoV 3CLpro by controlling its dimerization. Here, we studied N214A, another mutant with only a doubled dissociation constant but significantly abolished activity. Unexpectedly, N214A still adopts the dimeric structure almost identical to that of the wild-type (WT) enzyme. Thus, we conducted 30-ns molecular dynamics (MD) simulations for N214A, WT, and R298A which we previously characterized to be a monomer with the collapsed catalytic machinery. Remarkably, three proteases display distinctive dynamical behaviors. While in WT, the catalytic machinery stably retains in the activated state; in R298A it remains largely collapsed in the inactivated state, thus implying that two states are not only structurally very distinguishable but also dynamically well separated. Surprisingly, in N214A the catalytic dyad becomes dynamically unstable and many residues constituting the catalytic machinery jump to sample the conformations highly resembling those of R298A. Therefore, the N214A mutation appears to trigger the dramatic change of the enzyme dynamics in the context of the dimeric form which ultimately inactivates the catalytic machinery. The present MD simulations represent the longest reported so far for the SARS-CoV 3CLpro, unveiling that its catalysis is critically dependent on the dynamics, which can be amazingly modulated by the extra domain. Consequently, mediating the dynamics may offer a potential avenue to inhibit the SARS-CoV 3CLpro

Computational analysis of dynamic allostery and control in the SARS-CoV-2 main protease

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has no publicly available vaccine or antiviral drugs at the time of writing. An attractive coronavirus drug target is the main protease (Mpro, also known as 3CLpro) because of its vital role in the viral cycle. A significant body of work has been focused on finding inhibitors which bind and block the active site of the main protease, but little has been done to address potential non-competitive inhibition, targeting regions other than the active site, partly because the fundamental biophysics of such allosteric control is still poorly understood. In this work, we construct an elastic network model (ENM) of the SARS-CoV-2 Mpro homodimer protein and analyse its dynamics and thermodynamics. We found a rich and heterogeneous dynamical structure, including allosterically correlated motions between the homodimeric protease's active sites. Exhaustive 1-point and 2-point mutation scans of the ENM and their effect on fluctuation free energies confirm previously experimentally identified bioactive residues, but also suggest several new candidate regions that are distant from the active site, yet control the protease function. Our results suggest new dynamically driven control regions as possible candidates for non-competitive inhibiting binding sites in the protease, which may assist the development of current fragment-based binding screens. The results also provide new insights into the active biophysical research field of protein fluctuation allostery and its underpinning dynamical structure

Understanding the determinants for substrate recognition, regulation of enzymatic activity and the development of broad-spectrum inhibitors of coronavirus 3-chymotrypsin-like proteases

Coronaviruses include lethal human pathogens like severe acute respiratory syndrome coronavirus (SARS-CoV) and the recently emerged Middle-east respiratory coronavirus (MERS-CoV). Coronavirus also impact global economy by infecting farm animals like pigs (porcine epidemic diarrhea virus, PEDV), cows (bovine coronavirus, BCoV) and poultry (avian infectious bronchitis virus, IBV). Moreover, the global distribution of bats that naturally harbor one or more coronavirus strains heightens the likelihood of emergence of a novel highly pathogenic coronavirus in the near future. To combat infections of existing and emerging coronaviruses, it is important to identify coronavirus drug targets that can be utilized for the development of broad-spectrum anti-coronaviral therapeutics. Viral encoded 3-Chymotrypsin-like protease (3CLpro) is essential for viral polyprotein processing to release non-structural proteins that form the replicase complex machinery for viral genome replication. Due to its indispensable role in coronaviral replication, 3CLpro is an attractive drug target. Moreover, high sequence conservation in the vicinity of active site among 3CLpro proteases from different coronavirus subclasses make them an excellent target for the development of broad-spectrum therapeutics for coronavirus infections. The overarching goal of this project is to investigate enzymatic and structural properties of multiple 3CLpro enzymes encompassing different coronavirus subclasses. Understanding the determinants of structural and functional disparity between different 3CLpro enzymes and the factors regulating these properties will aid in the design of broad-spectrum inhibitors of 3CLpro enzymes

Structural, Stability, Dynamic and Binding Properties of the ALS-Causing T46I Mutant of the hVAPB MSP Domain as Revealed by NMR and MD Simulations

T46I is the second mutation on the hVAPB MSP domain which was recently identified from non-Brazilian kindred to cause a familial amyotrophic lateral sclerosis (ALS). Here using CD, NMR and molecular dynamics (MD) simulations, we characterized the structure, stability, dynamics and binding capacity of the T46I-MSP domain. The results reveal: 1) unlike P56S which we previously showed to completely eliminate the native MSP structure, T46I leads to no significant disruption of the native secondary and tertiary structures, as evidenced from its far-UV CD spectrum, as well as Cα and Cβ NMR chemical shifts. 2) Nevertheless, T46I does result in a reduced thermodynamic stability and loss of the cooperative urea-unfolding transition. As such, the T46I-MSP domain is more prone to aggregation than WT at high protein concentrations and temperatures in vitro, which may become more severe in the crowded cellular environments. 3) T46I only causes a 3-fold affinity reduction to the Nir2 peptide, but a significant elimination of its binding to EphA4. 4) EphA4 and Nir2 peptide appear to have overlapped binding interfaces on the MSP domain, which strongly implies that two signaling networks may have a functional interplay in vivo. 5) As explored by both H/D exchange and MD simulations, the MSP domain is very dynamic, with most loop residues and many residues on secondary structures highly fluctuated or/and exposed to bulk solvent. Although T46I does not alter overall dynamics, it does trigger increased dynamics of several local regions of the MSP domain which are implicated in binding to EphA4 and Nir2 peptide. Our study provides the structural and dynamic understanding of the T46I-causing ALS; and strongly highlights the possibility that the interplay of two signaling networks mediated by the FFAT-containing proteins and Eph receptors may play a key role in ALS pathogenesis

Protein dynamics at Eph receptor-ligand interfaces as revealed by crystallography, NMR and MD simulations

10.1186/2046-1682-5-2BMC Biophysics51

Structural Biology: Modeling applications and techniques at a glance

As recent advancements in biology shows, the molecular machines specially proteins, RNA and complex molecules play the main role of the so called cell functionality. It means a very big part of the system biology is concerned with the interactions of such molecular components. Drug industries and research institutes are trying hard to better understand the concepts underlying these interactions and are highly dependent on the issues regarding these molecular elements. However the costs for such projects are so high and in many cases these projects will be funded by governments or profit making companies. With this in mind it has to be said that the techniques like stimulation are always a very good candidate to decrease such costs and to provide scientists with a bright future of the project results before undergoing costly experiments. However the costs involved projects that determine an approximation for the problem is not that much high but they are also costly. So it is of utmost importance to invent special techniques for the concept of stimulation that can also decrease the project costs and also predict much accurately. Since the system biology and proteomics as the study of the proteins and their functions are in the center of consideration for the purpose of drug discovery, understanding the cell functionalities and the underlying causes behind diseases; so we need advance software and algorithms that can predict the structure of the molecular components and to provide researchers with the computational tools to analyze such models. In this paper we make review of the importance of molecular modeling, its limitations and applications

Atomistic graph analysis of protein dimers in disease

Proteins are fundamental components of biological processes thus, they are often termed the molecular machinery of life. They commonly form dimers, in a process that is often essential for their functionality. Given the ubiquitous nature of protein regulation, many diseases are based on malfunctioning proteins and inhibiting them by binding to the active site is a widely chosen approach in drug development. However, due to acquired resistance mechanisms or high off-target effects, the active site might not always be a viable approach. This work presents an atomistic, structural investigation of dimeric proteins in the context of major disease processes, where we provide insights into potential alternative drug targeting approaches. In this Thesis, novel diffusion-based methods are applied to characterise the intra-structural connectivity and signalling of protein dimers. The basis of our methods is the description of proteins as atomistic, energy-weighted graphs, where every atom represents a node, and every bond or interaction is encoded as a weighted edge. These graphs facilitate the study of connectivity and signal propagation within the protein through diffusion processes on the atom (node) and bond (edge) space. Two complementary methodologies are applied here, Markov Transients and bond-to-bond propensities, which have been successfully used in the context of allosteric site detection, the study of protein-protein interactions and the investigation of allosteric signalling on an atomistic level. This work explores the extension of these methodologies onto protein dimers and presents the investigation of allosteric mechanisms in three disease-relevant study systems: 1. Estrogen receptor alpha (ERα) is a homodimer and the main driver in breast cancer (BC) development and progression. Current chemotherapies based on inhibiting ERα become ineffective when recurrent tumours develop resistance against anti-estrogens. Our methodologies validate the molecular mechanism in ERα, and we further establish the prevalent role of the dimer interface in the inhibition process. 2. The main protease (Mpro) of the coronavirus SARS-CoV-2 is essential for virus replication in an early step of the viral life cycle. Since the beginning of 2020, we have seen this virus causing a global pandemic of COVID-19, with over 285 million cases of infection and over 5.5 million deaths by the end of 2021. To aid in combating COVID-19, we predict highly connected allosteric hotspots and provide insights into how the disruption of the obligatory Mpro dimerisation presents a fruitful approach. 3. Cyclin-dependent kinases (CDKs) 4 and 6 are two essential cell cycle regulators that are often associated with cancer development, and in BC, their inhibition is part of an effective combinatorial treatment. This work contributes to understanding their activation process in complex with D-type cyclins and sheds light on the differential inhibitor patterns seen for CDKs. By exploring these three systems with atomistic graph analysis, we describe intra-complex communication essential for activation in all three proteins. We further present implications for the respective dimer interface connectivities and how they could be a fruitful drug target. We conclude that ERα, the SARS-CoV-2 Mpro and CDK4/6 can be disrupted over allosteric mechanisms that include their dimer interfaces. These results provide scope for targeted drug development and provide a valuable contribution to the ongoing efforts to find efficient treatments for BC and COVID-19.Open Acces