Reaction kinetics of catalyzed competitive heteropolymer cleavage

The HIV-1 Nucleocapsid Regulates Its Own Condensation by Phase-Separated Activity-Enhancing Sequestration of the Viral Protease during Maturation

A growing number of studies indicate that mRNAs and long ncRNAs can affect protein populations by assembling dynamic ribonucleoprotein (RNP) granules. These phase-separated molecular ‘sponges’, stabilized by quinary (transient and weak) interactions, control proteins involved in numerous biological functions. Retroviruses such as HIV-1 form by self-assembly when their genomic RNA (gRNA) traps Gag and GagPol polyprotein precursors. Infectivity requires extracellular budding of the particle followed by maturation, an ordered processing of ∼2400 Gag and ∼120 GagPol by the viral protease (PR). This leads to a condensed gRNA-NCp7 nucleocapsid and a CAp24-self-assembled capsid surrounding the RNP. The choreography by which all of these components dynamically interact during virus maturation is one of the missing milestones to fully depict the HIV life cycle. Here, we describe how HIV-1 has evolved a dynamic RNP granule with successive weak–strong–moderate quinary NC-gRNA networks during the sequential processing of the GagNC domain. We also reveal two palindromic RNA-binding triads on NC, KxxFxxQ and QxxFxxK, that provide quinary NC-gRNA interactions. Consequently, the nucleocapsid complex appears properly aggregated for capsid reassembly and reverse transcription, mandatory processes for viral infectivity. We show that PR is sequestered within this RNP and drives its maturation/condensation within minutes, this process being most effective at the end of budding. We anticipate such findings will stimulate further investigations of quinary interactions and emergent mechanisms in crowded environments throughout the wide and growing array of RNP granules.

Fine-Tuning of Sequence Specificity by Near Attack Conformations in Enzyme-Catalyzed Peptide Hydrolysis

The catalytic role of near attack conformations (NACs), molecular states that lie on the pathway between the ground state (GS) and transition state (TS) of a chemical reaction, is not understood completely. Using a computational approach that combines Bürgi–Dunitz theory with all-atom molecular dynamics simulations, the role of NACs in catalyzing the first stages of HIV-1 protease peptide hydrolysis was previously investigated using a substrate that represents the recognized SP1-NC cleavage site of the HIV-1 Gag polyprotein. NACs were found to confer no catalytic effect over the uncatalyzed reaction there ( Δ Δ G N ‡ ∼ 0 kcal/mol). Here, using the same approach, the role of NACs across multiple substrates that each represent a further recognized cleavage site is investigated. Overall rate enhancement varies by | Δ Δ G ‡ | ∼ 12–15 kcal/mol across this set, and although NACs contribute a small and approximately constant barrier to the uncatalyzed reaction (< Δ G N ‡ u > = 4.3 ± 0.3 kcal/mol), they are found to contribute little significant catalytic effect ( | Δ Δ G N ‡ | ∼ 0–2 kcal/mol). Furthermore, no correlation is exhibited between NAC contributions and the overall energy barrier ( R 2 = 0.01). However, these small differences in catalyzed NAC contributions enable rates to match those required for the kinetic order of processing. Therefore, NACs may offer an alternative and subtle mode compared to non-NAC contributions for fine-tuning reaction rates during complex evolutionary sequence selection processes—in this case across cleavable polyproteins whose constituents exhibit multiple functions during the virus life-cycle.

Reaction-diffusion basis of retroviral infectivity

Retrovirus particle (virion) infectivity requires diffusion and clustering of multiple transmembrane envelope proteins (Env₃) on the virion exterior, yet is triggered by protease-dependent degradation of a partially occluding, membrane-bound Gag polyprotein lattice on the virion interior. The physical mechanism underlying such coupling is unclear and only indirectly accessible via experiment. Modelling stands to provide insight but the required spatio-temporal range far exceeds current accessibility by all-atom or even coarse-grained molecular dynamics simulations. Nor do such approaches account for chemical reactions, while conversely, reaction kinetics approaches handle neither diffusion nor clustering. Here, a recently developed multiscale approach is considered that applies an ultra-coarse-graining scheme to treat entire proteins at near-single particle resolution, but which also couples chemical reactions with diffusion and interactions. A model is developed of Env₃ molecules embedded in a truncated Gag lattice composed of membrane-bound matrix proteins linked to capsid subunits, with freely diffusing protease molecules. Simulations suggest that in the presence of Gag but in the absence of lateral lattice-forming interactions, Env₃ diffuses comparably to Gag-absent Env₃ Initial immobility of Env₃ is conferred through lateral caging by matrix trimers vertically coupled to the underlying hexameric capsid layer. Gag cleavage by protease vertically decouples the matrix and capsid layers, induces both matrix and Env₃ diffusion, and permits Env₃ clustering. Spreading across the entire membrane surface reduces crowding, in turn, enhancing the effect and promoting infectivity.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.

Gag-Pol processing during HIV-1 virion maturation: a systems biology approach

Proteolytic processing of Gag and Gag-Pol polyproteins by the viral protease (PR) is crucial for the production of infectious HIV-1, and inhibitors of the viral PR are an integral part of current antiretroviral therapy. The process has several layers of complexity (multiple cleavage sites and substrates; multiple enzyme forms; PR auto-processing), which calls for a systems level approach to identify key vulnerabilities and optimal treatment strategies. Here we present the first full reaction kinetics model of proteolytic processing by HIV-1 PR, taking into account all canonical cleavage sites within Gag and Gag-Pol, intermediate products and enzyme forms, enzyme dimerization, the initial auto-cleavage of full-length Gag-Pol as well as self-cleavage of PR. The model allows us to identify the rate limiting step of virion maturation and the parameters with the strongest effect on maturation kinetics. Using the modelling framework, we predict interactions and compensatory potential between individual cleavage rates and drugs, characterize the time course of the process, explain the steep dose response curves associated with PR inhibitors and gain new insights into drug action. While the results of the model are subject to limitations arising from the simplifying assumptions used and from the uncertainties in the parameter estimates, the developed framework provides an extendable open-access platform to incorporate new data and hypotheses in the future.

Patient-specific modelling in drug design, development and selection including its role in clinical decision-making

Genomics has made enormous progress in the twelve years since the publication of the first draft human genome sequence, but it has not yet been translated into the clinic. Despite spiralling development costs, the number of new drug registrations is not increasing. One reason for this lies in the genetic complexity of disease. Most diseases involve dysregulation in pathways that involve many genes, and many (including most cancers) are themselves genetically heterogeneous. Systems biology involves the multi-level simulation of physiology, cell biology and biochemistry using complex computational techniques. We show here using case studies in cancer and HIV how such computational models, and particularly models based on individual patient data, can be used for drug design and development, and in the selection of the appropriate treatment for a given patient in the face of resistance mutations. If these techniques are to be adopted in routine clinical practice, clinicians will need better training in modern approaches to the integrated analysis of large-scale heterogeneous data and multi-scale models, while developers will need to provide much more usable tools. Investment in computational infrastructure is needed so that results can be returned on clinically relevant timescales and data warehouses designed with data protection as well as accessibility in mind.

From base pair to bedside: molecular simulation and the translation of genomics to personalized medicine

Despite the promises made that genomic sequencing would transform therapy by introducing a new era of personalized medicine, relatively few tangible breakthroughs have been made. This has led to the recognition that complex interactions at multiple spatial, temporal, and organizational levels may often combine to produce disease. Understanding this complexity requires that existing and future models are used and interpreted within a framework that incorporates knowledge derived from investigations at multiple levels of biological function. It also requires a computational infrastructure capable of dealing with the vast quantities of data generated by genomic approaches. In this review, we discuss the use of molecular modeling to generate quantitative and qualitative insights at the smallest scales of the systems biology hierarchy, how it can play an important role in the development of a systems understanding of disease and in the application of such knowledge to help discover new therapies and target existing ones on a personal level.