Structure Based Affinity Maturation and Characterizing of SARS-CoV Antibody CR3022 against SARS-CoV-2 by Computational and Experimental Approaches

Structure-Based Optimization of One Neutralizing Antibody against SARS-CoV-2 Variants Bearing the L452R Mutation

Neutralizing antibodies (nAbs) play an important role against SARS-CoV-2 infections. Previously, we have reported one potent receptor binding domain (RBD)-binding nAb Ab08 against the SARS-CoV-2 prototype and a panel of variants, but Ab08 showed much less efficacy against the variants harboring the L452R mutation. To overcome the antibody escape caused by the L452R mutation, we generated several structure-based Ab08 derivatives. One derivative, Ab08-K99E, displayed the mostly enhanced neutralizing potency against the Delta pseudovirus bearing the L452R mutation compared to the Ab08 and other derivatives. Ab08-K99E also showed improved neutralizing effects against the prototype, Omicron BA.1, and Omicron BA.4/5 pseudoviruses. In addition, compared to the original Ab08, Ab08-K99E exhibited high binding properties and affinities to the RBDs of the prototype, Delta, and Omicron BA.4/5 variants. Altogether, our findings report an optimized nAb, Ab08-K99E, against SARS-CoV-2 variants and demonstrate structure-based optimization as an effective way for antibody development against pathogens.

Graphene Field Effect Biosensor for Concurrent and Specific Detection of SARS-CoV-2 and Influenza

The SARS-CoV-2 pandemic has highlighted the need for devices capable of carrying out rapid differential detection of viruses that may manifest similar physiological symptoms yet demand tailored treatment plans. Seasonal influenza may be exacerbated by COVID-19 infections, increasing the burden on healthcare systems. In this work, we demonstrate a technology based on liquid-gated graphene field-effect transistors (GFETs), for rapid and ultraprecise sensing and differentiation of influenza and SARS-CoV-2 surface protein. Most distinctively, the device consists of 4 onboard GFETs arranged in a quadruple architecture, where each quarter is functionalized individually (with either antibodies or chemically passivated control) but measured jointly. The sensor platform was tested against a range of concentrations of viral surface proteins from both viruses with the lowest tested and detected concentration at ∼50 ag/mL, or 88 zM for COVID-19 and 227 zM for Flu, which is 5-fold lower than the values reported previously on a similar platform. Unlike the classic real-time polymerase chain reaction test, which has a turnaround time of a few hours, the graphene technology presents an ultrafast response time of ∼10 s even in complex and clinically relevant media such as saliva. Thus, we have developed a multianalyte, highly sensitive, and fault-tolerant technology for rapid diagnostic of contemporary, emerging, and future pandemics.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

Experimental and computational approaches to characterize a novel amidase that initiates the biodegradation of the herbicide propanil in Bosea sp. P5

The herbicide propanil and its major metabolite 3,4-dichloroaniline (3,4-DCA) are difficult to biodegrade and pose great health and environmental risks. However, studies on the sole or synergistic mineralization of propanil by pure cultured strains are limited. A two-strain consortium (Comamonas sp. SWP-3 and Alicycliphilus sp. PH-34), obtained from a swep-mineralizing enrichment culture that can synergistically mineralize propanil, has been previously reported. Here, another propanil degradation strain, Bosea sp. P5, was successfully isolated from the same enrichment culture. A novel amidase, PsaA, responsible for initial propanil degradation, was identified from strain P5. PsaA shared low sequence identity (24.0-39.7 %) with other biochemically characterized amidases. PsaA exhibited optimal activity at 30 °C and pH 7.5 and had k_cat and K_m values of 5.7 s^-1 and 125 μM, respectively. PsaA could convert the herbicide propanil to 3,4-DCA but exhibited no activity toward other herbicide structural analogs. This catalytic specificity was explained by using propanil and swep as substrates and then analyzed by molecular docking, molecular dynamics simulation and thermodynamic calculations, which revealed that Tyr138 is the key residue that affects the substrate spectrum of PsaA. This is the first propanil amidase with a narrow substrate spectrum identified, providing new insights into the catalytic mechanism of amidase in propanil hydrolysis.

Complexity of Viral Epitope Surfaces as Evasive Targets for Vaccines and Therapeutic Antibodies

The dynamic interplay between virus and host plays out across many interacting surfaces as virus and host evolve continually in response to one another. In particular, epitope-paratope interactions (EPIs) between viral antigen and host antibodies drive much of this evolutionary race. In this review, we describe a series of recent studies examining aspects of epitope complexity that go beyond two interacting protein surfaces as EPIs are typically understood. To structure our discussion, we present a framework for understanding epitope complexity as a spectrum along a series of axes, focusing primarily on 1) epitope biochemical complexity (e.g., epitopes involving N-glycans) and 2) antigen conformational/dynamic complexity (e.g., epitopes with differential properties depending on antigen state or fold-axis). We highlight additional epitope complexity factors including epitope tertiary/quaternary structure, which contribute to epistatic relationships between epitope residues within- or adjacent-to a given epitope, as well as epitope overlap resulting from polyclonal antibody responses, which is relevant when assessing antigenic pressure against a given epitope. Finally, we discuss how these different forms of epitope complexity can limit EPI analyses and therapeutic antibody development, as well as recent efforts to overcome these limitations.