Forces and Disease: Electrostatic force differences caused by mutations in kinesin motor domains can distinguish between disease-causing and non-disease-causing mutations

Lin, Liang-In; Jia, Zhe; Peng, Yunhui; Godar, Subash; Getov, Ivan; Teng, Shaolei; Alper, Joshua; Alexov, Emil

doi:10.1038/s41598-017-08419-7

Cited by 28 publications

(24 citation statements)

References 78 publications

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“…The affinity of the S and ACE2 and the stability of RBD-ACE2 complex are hence important to be investigated. We have applied the structure-based tools to quantitatively assess the effects of damaging mutations on protein stability and proteinprotein interaction (18)(19)(20). In the present study, we applied saturation mutagenesis to investigate 18,354 missense mutations in SARS-CoV-2 S, 3,705 mutations in SARS-CoV-2 RBD, and 11,324 mutations in hACE2.…”

Section: Introductionmentioning

confidence: 99%

Systemic Effects of Missense Mutations on SARS-CoV-2 Spike Glycoprotein Stability and Receptor Binding Affinity

Teng

Sobitian

Rhoades

et al. 2020

Preprint

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The spike (S) glycoprotein of SARS-CoV-2 is responsible for the binding to the permissive cells.The receptor-binding domain (RBD) of SARS-CoV-2 S protein directly interacts with the human angiotensin-converting enzyme 2 (ACE2) on the host cell membrane. In this study, we used computational saturation mutagenesis approaches, including structure-based energy calculations and sequence-based pathogenicity predictions, to quantify the systemic effects of missense mutations on SARS-CoV-2 S protein structure and function. A total of 18,354 mutations in S protein were analyzed and we discovered that most of these mutations could destabilize the entire S protein and its RBD. Specifically, residues G431 and S514 in SARS-CoV-2 RBD are important for S protein stability. We analyzed 384 experimentally verified S missense variations and revealed that the dominant pandemic form, D614G, can stabilize the entire S protein. Moreover, many mutations in N-linked glycosylation sites can increase the stability of the S protein. In addition, we investigated 3,705 mutations in SARS-CoV-2 RBD and 11,324 mutations in human ACE2 and found that SARS-CoV-2 neighbor residues G496 and F497 and ACE2 residues D355 and Y41 are critical for the RBD-ACE2 interaction. The findings comprehensively provide potential target sites in the development of drugs and vaccines against COVID-19.Coronaviruses are a large family of enveloped RNA viruses typically transmitted from animals to animals. These viruses are usually found in bats, birds, and mammals (1), but seven coronavirus members are found to infect humans. The paradigm shift in the mode of transmission of three pathogenic coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severe acute respiratory syndrome (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), has resulted in recent outbreaks. The SARS-CoV epidemic began in Shunde, Guangdong, China, in November 2002. It ended in 2003 with more than 8000 cases in over 28 countries and ~800 deaths. The presence of a SARS-CoV-like coronavirus in bats indicated that the natural reservoir of SARS-CoV is horseshoe bat (2, 3). The MERS-CoV epidemic began in Saudi-Arabia in June 2012, and the transmission of MERS-CoV crossed the Arab peninsula to nearby countries. Scientists revealed that the Arabian camel (dromedaries) is the reservoir host to MERS-CoV, and they also spread the virus to humans. As of January 2020, the World Health Organization (WHO) reported 2,519 MERS-CoV cases in 27 countries and ~866 deaths. Although both SARS-CoV and MERS-CoV were transmitted from animals to humans, human to human transmission was found plausible (2). The most recent outbreak of Coronavirus Disease 2019 (COVID-19) is caused by a novel coronavirus, SARS-CoV-2. The virus is closely related to the SARS-like CoV, RaTG13 virus which is found in bats (4). SARS-CoV-2 is so far the most pathogenic coronavirus. As of May 23, 2020, WHO reported over 5 million confirmed cases of COVID-19 in 216 countries, resulting in > 331,000...

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Section: Introductionmentioning

confidence: 99%

Systemic Effects of Missense Mutations on SARS-CoV-2 Spike Glycoprotein Stability and Receptor Binding Affinity

Teng

Sobitian

Rhoades

et al. 2020

Preprint

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“…The main differences between these two predicted states are the hot spots residues identified for each situation, even though some of these hot spots repeat within the interface for both approaches (Tables 1 and 2). Several studies have shown how electrostatic forces contribute to PPIs, including those related to diseases development [67][68][69]. Figure 1C and 1D show a predicted mode of interaction between eNOS and p53 regarding hydrophobic-favored and Van der Waals-favored coefficients, respectively.…”

Section: Resultsmentioning

confidence: 95%

Therapeutic Design of Peptide Modulators of the Interaction Between eNOS and p53 in Atherosclerosis

Ds¹,

Lp²,

Am³

et al. 2019

JICOA

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Atherosclerosis is a cardiovascular disease featuring a chronic inflammation due to the accumulation of lipids within the tunica intima of arteries. The development of the disease depends on dynamic changes in the vascular biology. Immune system cells directly influence the pathogenesis of atherosclerosis during the inflammatory process. Currently, atherosclerosis diagnosis is performed by non-invasive or invasive methods depending on the type of arteries that are being investigated. New diagnostic and therapeutic procedures should improve the quality of life of patients. Some of the genes that could be biomarkers of cardiovascular diseases are TP53 and eNOS. The protein p53 is recognized as a tumor suppressor protein that controls DNA repair, cell cycle progression or arrest and apoptosis. These functions that p53 exerts are well known and some other functions are being investigated, such as its role in the cardiovascular system. The eNOS gene regulates the levels of nitric oxide, which is vital for several intracellular biological functions, such as vasodilation, vascular homeostasis, protection of arteries against injuries, cellular growth, signaling pathways and immune response among others. Here, we used an in-silico approach to predict four models of interaction between clinically important proteins (eNOS and p53), to predict the interface of interaction and to rationally design modulating peptides to be tested in vitro and in vivo and possibly used as a therapeutic agent.

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“…Electrostatic forces are frequently omitted from the analysis of e®ect of mutations, however, recently it was demonstrated that the changes of electrostatic forces due to mutations can be used to discriminate pathogenic from benign mutations. 73 There are no many resources available for modeling electrostatic forces in molecular biology with the prominent exception of DelPhiForce. 74,75 This tool allows for modeling the electrostatic forces acting on individual atom(s), residue(s) or molecular partners.…”

Section: Electrostatic Forcesmentioning

confidence: 99%

Computational chemistry methods to investigate the effects caused by DNA variants linked with disease

Koirala

Alexov

2019

J. Theor. Comput. Chem.

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Computational chemistry offers variety of tools to study properties of biological macromolecules. These tools vary in terms of levels of details from quantum mechanical treatment to numerous macroscopic approaches. Here, we provide a review of computational chemistry algorithms and tools for modeling the effects of genetic variations and their association with diseases. Particular emphasis is given on modeling the effects of missense mutations on stability, conformational dynamics, binding, hydrogen bond network, salt bridges, and pH-dependent properties of the corresponding macromolecules. It is outlined that the disease may be caused by alteration of one or several of above-mentioned biophysical characteristics, and a successful prediction of pathogenicity requires detailed analysis of how the alterations affect the function of involved macromolecules. The review provides a short list of most commonly used algorithms to predict the molecular effects of mutations as well.

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Forces and Disease: Electrostatic force differences caused by mutations in kinesin motor domains can distinguish between disease-causing and non-disease-causing mutations

Cited by 28 publications

References 78 publications

Systemic Effects of Missense Mutations on SARS-CoV-2 Spike Glycoprotein Stability and Receptor Binding Affinity

Systemic Effects of Missense Mutations on SARS-CoV-2 Spike Glycoprotein Stability and Receptor Binding Affinity

Therapeutic Design of Peptide Modulators of the Interaction Between eNOS and p53 in Atherosclerosis

Computational chemistry methods to investigate the effects caused by DNA variants linked with disease

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