Current Research Interests

Multiscale biophysics of molecular sociology

Sub-cellular biology is governed by interactions between many biomolecules that fleetingly assemble into architectures in the crowded cytoplasm, sometimes compartmentalised by membranes but even phase separating into distinct membraneless organelles. This 'molecular sociology' is often coupled to and governed by networks of biochemical reactions and affected by interactions of its constituents at several scales of space and time - from microseconds to minutes and Angstroms to micrometres.

We are developing a coupled AI-physics-based computational modelling framework that can follow the spatial dynamics of such molecular sociological processes across multiple scales - addressing conformational changes of biomolecules, molecular binding kinetics and emergent self-organising properties of the resulting 'molecular sociology' in the sub-cellular environment.

This enables us to generate theoretical predictions of processes and architectures that may arise under different conditions in the cytoplasm that can then be tested by experiment. These efforts drive our aim to gain a deeper understanding of the physics of soft condensed active matter.

De novo protein design

Proteins are the workhorses of living things. They perform virtually all the functions required for molecular biological life. The majority of proteins do this by folding from the linear chains of amino acids they are made of into specific three-dimensional structures that are key to their function. Predicting the folded structure of proteins from their amino acid sequence has been a 50-year grand challenge. Recent AI-based approaches such as AlphaFold and RosettaFold have achieved transformational success in accurately predicting protein structure – allowing us to enter a structurally-rich era in biology.

Protein design is the inverse problem. From a list of desired structural and functional features of a protein is it possible to design or predict an amino acid sequence that will fulfil those features? Conventionally, computational approaches for protein design often use existing template structures of proteins as a starting point for design. De novo protein design by contrast is the design of novel proteins, completely from scratch, without a starting template.

Using AI-based approaches that build on the richness of available structural data we are developing novel frameworks for de novo protein design [1-2]. These approaches allow us to explore sequence space well beyond that explored by evolution and design new proteins that have never existed before in Nature. Such approaches can be tailored to design proteins that can bind strongly to other proteins, self-assemble into multimers, and even change conformation in different settings.

[1] Jendrusch, M., Korbel, J. O., & Sadiq, S. K. (2021) bioRxiv. AlphaDesign: A de novo protein design framework based on AlphaFold. https://doi.org/10.1101/2021.10.11.463937
[2] Jendrusch, M., Korbel, J. O., & Sadiq, S. K. (2022) US Patent Application No. 63/329,522

Some examples of our work

Retrovirus Assembly and Maturation

Particle-based reaction-diffusion simulation of HIV-1 spike membrane glycoproteins (red) initially trapped by the matrix-capsid (blue-green) becoming mobile during maturation by viral protease (cyan).

Retrovirus maturation is a remarkable example involving 100nm-scale self-assembly, auto-catalysed chemical degradation and architectural transformation of ~10,000 constituent biomolecules in minutes, in a sequence of steps that need to be carefully timed. Whilst reaction kinetics approaches are good for modelling the change of concentrations of various species over time, they provide no spatial description, nor do they handle diffusion. On the other hand, all-atom and coarse-grained molecular dynamics (MD) simulations struggle to access realistic timescale required to follow large scale macromolecular assembly processes, such as virus capsid assembly. Moreover they do not handle phenomenological chemical reactions, such as polyprotein cleavage. Recent development of ultra-coarse-grained (UCG) interacting particle-based reaction diffusion (iPRD) simulation approaches has now made a range of reaction-coupled clustering problems accessible.

We have developed a particle reaction diffusion approach to model retroviral infectivity that enables the spatiotemporal linkage between degradation of a truncated hexameric Gag lattice and diffusional clustering of envelope proteins to be followed. The model accounts for the basic physical determinants of infectivity and to our knowledge is the first spatiotemporal model of partial retrovirus maturation processes that couples reaction to diffusion.

Sadiq, S.K. (2016). Phil Trans R Soc A. Reaction-diffusion basis of retroviral infectivity. 374:20160148

Accelerated enzyme kinetics in phase-separated ribonucleoprotein condensates

Proteins diffusing in and around an RNA granule inside the cell, against a backdrop of other RNA granules (artistic impression, picture: Ina Poehner, Kashif Sadiq).

Phase-separation has become established as a fundamental phenomenon in molecular biology - whereby mixtures of proteins and/or nucleic acids spontaneously separate into a distinct phase from the rest of the cytoplasm and form granular membraneless organelles. Both the underlying physical determinants and biological role of such phenomena still remain incompletely understood.

The ribonucleoprotein (RNP) of HIV forms a phase-separated condensate both in vitro and in vivo. We use it as a model system to explore the potential biological roles of phase separation. In particular, one hypothesis is that enzyme kinetics can be modulated in such compartments. As the immature nucleocapsid of HIV is itself a cleavage substrate of the viral protease, this system allows us to investigate the rate of enzyme catalysis in the context and absence of the viral RNP.

Through a combination of AFM measurements of dynamic RNP condensation, enzymatic assays and the development of a kinetic polymer model, we show that the rate of proteolysis is indeed accelerated in such condensates and this is quantitatively consistent with an increase in concentration of absorbed enzyme within the condensate.

S. Lyonnais*‡, S.K. Sadiq*‡ C. Lorca-Oró, L. Dufau, S. Nieto Marquez, T. Escriba, N. Gabrielli, X. Tan, M. Ouizougun-Oubari, J. Okoronkwo, M. Reboud-Ravaux, J. M. Gatell, R. Marquet, J.-C. Paillart, A. Meyerhans, C. Tisné, R. J.Gorelick, and G. Mirambeau*‡ (2019) bioRxiv, The HIV-1 ribonucleoprotein dynamically regulates its condensate behavior and drives acceleration of protease activity through membrane-less granular phase separation, 528638; doi: https://doi.org/10.1101/528638

Molecular binding and conformational kinetics

Molecular binding underpins the whole of biology. And yet predicting how biomolecules such as proteins, ligands and nucleic acids bind/unbind to each other, and how fast, is very difficult - not least because such molecules have complicated 3D structures but even more challengingly because many are flexible and interchange between a variety of conformations. Therefore, understanding how biomolecules bind to each other often requires simultaneously understanding how they change conformation.

We apply a variety of molecular simulation methods to characterise binding and conformational changes in biomolecules. This ranges from all-atom MD simulations, coarse-grained MD and Brownian dynamics approaches. We also develop statistical physics methods, such as Markov state models and accelerated MD, that aim to combine the accuracy of computationally demanding methods like MD with the efficiency of more coarse-grained methods.

These methods have application in the prediction of conformationally flexible protein-protein and protein-ligand binding kinetics but also in the characterisation of extremely flexible proteins, how such biomolecules function in intermediate or precursor states and provide insight into the nature of metamorphic proteins - whereby the same amino acid sequence can exhibit completely different folds.

Critical self-activation of immature HIV-1 protease

Autocatalysis by HIV-1 protease: An immature pseudo-folded protease binding and recognising its own N-terminal tail during all-atom molecular dynamics simulations.

We investigated the structural basis for the self-activation of HIV-1 protease. The precursor protease emerges from an embedded dimerized form of the polyproteins that it cleaves. Using large-scale molecular dynamics simulations on the GPUGRID supercomputing infrastructure coupled to the development of novel analysis algorithms, we first demonstrated that the enzyme can exist in multiple conformations including the substrate bound conformation, even in the absence of the substrate. Then, by incorporating theoretical descriptions in transition path theory, we determined the structural and kinetic pathway of self-activation. The N-terminal of the protease, which is usually tightly folded in the dimer interface far from the active site, can in the immature protease have enough flexibility to bind to the active site thus triggering self-activation. This was the first all-atom structural description of the process. The structures that emerge from this work form the basis for a new target for HIV-1 therapy.

Sadiq, S. K. and De Fabritiis, G. (2010). Proteins: Struct Funct Bioinf. Explicit solvent dynamics and energetics of HIV-1 protease flap-opening and closing, 78: 2873–2885.
Sadiq, S. K., Noé, F. and De Fabritiis, G. (2012). Proc Natl Acad Sci USA. Kinetic characterization of the critical step in HIV-1 protease maturation. 109 (50), 20449-20454.

Domain rearrangements in NNRTI-bound HIV-1 Reverse Transcriptase (RT)

Molecular dynamics simulation of the thumb domain (red) of HIV-1 reverse transcriptase closing towards the fingers (cyan), despite a non-nucleoside reverse transcriptase inhibitor (NNRTI), efavirenz, being bound to keep it wedged open.

Function of HIV-1 reverse transcriptase requires the ability for one of its domains, the thumb domain to open and close during reverse transcription. A widely held view about the mechanism of NNRTIs was that they locked the “thumb” domain in an open conformation. We demonstrated using all-atom MD simulations that the thumb domain can close even in NNRTI-bound HIV-1 RT. This means that rather than an inducing an absolute locking mechanism NNRTIs must change the conformational equilibrium between open and closed forms of the thumb.

Wright, D.W.%, Sadiq, S.K. %, De Fabritiis, G. and Coveney, P.V. (2012). J Am Chem Soc. Thumbs down for HIV: Domain level rearrangements do occur in the NNRTI  bound HIV-1 Reverse Transcriptase. 134 (31), 12885–12888.

Investigating the metamorphic nature of the HIV-1 fusion peptide

Metamorphic switching of the HIV-1 fusion peptide from an alpha-helix fold into a beta-hairpin fold during an all-atom molecular dynamics simulation.

Many proteins do not have a stable tertiary structure yet are still functional, either because they transiently form folded structures or because they exhibit a pattern of dynamical interactions. The fusion peptide of HIV is an example. It is unstructured in solvent yet must form alpha-helical and/or beta-sheets to embed in host cell membranes thus forming the viral anchor that leads to membrane fusion. By designing and implementing large-scale MD simulations and developing novel analysis algorithms for clustering secondary structures, we have shown that the fusion peptide forms a small complex ensemble of structures even in solvent as well as unstructured conformations. This implies that viral fusion is coordinated by the kinetic interplay between these conformers.

Venken, T., Voet, A., De Maeyer, M., De Fabritiis, G. and Sadiq, S.K. (2013). J Chem  Theor Comput. Rapid conformational fluctuations of disordered HIV-1 fusion peptide in  solution. 9 (7), 2870–2874.

Previous Research

Molecular dynamics simulations and biomolecular binding free energy calculations

MD simulations of drug resistance in HIV-1 protease

We discovered a mutation-assisted lateral drug escape mechanism from the HIV-1 protease active site. Characteristic drug resistant mutant strains were shown to take advantage of extra coupling between the secondary-structure elements known as the “flaps” of the protease to induce the first stages of lateral dissociation from the active site. This led to the notion that a fully open active site is not necessary for inhibitor dissociation and revealed a new mechanism by which mutation-accelerated dissociation may occur.

Sadiq, S. K., Wan, S. and Coveney, P. V. (2007). Insights into a mutation-assisted lateral drug escape
mechanism from the HIV-1 protease active site. 46 (51), 14865 -14877.

Accurate and reproducible binding affinity calculation methodologies

We also developed a methodology for determining absolute inhibitor binding free energies to HIV-1 protease from MD simulations. The sensitivity of the approach allowed drug resistant mutations to be thermodynamically distinguished in excellent agreement with experiment. This guided the development and optimization of a rigorous absolute binding affinity methodology using explicit solvent and umbrella sampling techniques that made use of distributed computing resources and which came within 1 kcal/mol of absolute accuracy to experiment.

Stoica, I., Sadiq, S. K. and Coveney, P. V. (2008). J Am Chem Soc. Rapid and accurate prediction of binding free energies for saquinavir-bound HIV-1 proteases. 130, 2639-2648.
Sadiq, S. K., Wright, D. W., Kenway, O. A. and Coveney, P. V. (2010). J Chem Inf Model. Accurate ensemble molecular dynamics binding free energy ranking of  multidrug-resistant HIV-1 proteases, 50(5), 890–905.
Buch, I.%, Sadiq, S. K.% and De Fabritiis, G. (2011). J Chem Theor Comput. Optimizing potential of mean force calculations of standard binding free energy, 7, 1765–1772.

Development of automated binding affinity calculator for drug resistance in HIV for use in patient-specific clinical decision making software

The above methodological work formed the basis for the molecular component of the EU 6th Framework project “ViroLab” where computed thermodynamic data on inhibitor-mutant binding is integrated with additional resistance determination software to provide enhanced clinical decision support. We developed a computational framework that automated the calculation of protein-ligand binding affinities and which formed the basis of an initiative to provide enhanced phenotyopic clinical decision support on a patient specific basis, specifically by using viral genotypic information unique to a given patient and high performance computing resources. This required achieving successful management of the challenges faced in using state-of-the-art supercomputing infrastructures. The research has intersected with the EU 7th framework project “VPH”, forming an example of direct utilization of molecular level scientific models to address higher scale physiological behavior. The framework has subsequently been used to successfully distinguish between outputs from two discordant decision support software analyzing real patient genotypes.

Sadiq, S. K., Zasada, S. J., Wright, D., Stoica, I., and Coveney, P. V. (2008). J Chem Inf Model. Automated molecular simulation based binding affinity calculator for ligand-bound HIV-1 proteases. 48, 1909-1919.
Sadiq, S. K., Mazzeo, M. D., Zasada, S. J., Manos, S., Stoica, I., Gale, C. V., Watson, S.  J., Kellam, P., Brew, S. and Coveney, P. V. (2008). Phil Trans R Soc A. Patient-specific  simulation as a basis for clinical decision making. 366, 3199-3219.

Systems biology approaches towards HIV maturation

Development of mathematical framework for enzyme-catalyzed (Gag and GagPol) cleavage

We derived a general theoretical reaction kinetics formulation for the complete degradation of heteropolymers. This can be applied to HIV Gag chains and allows prediction of the liberation rate of key components involved in HIV maturation such as capsid proteins. This has been extended to the degradation of Gag and GagPol polyproteins, including self-activation of the protease and constitutes the first detailed reaction kinetics model of HIV maturation.

Sadiq, S. K., Konnyu, B., Muller, V. and Coveney, P.V. (2011) J Phys Chem B. Reaction Kinetics of Catalyzed Competitive Heteropolymer Cleavage, 115, 11017–  11027.
Konnyu, S. K. Sadiq, T. Turanyi, R. Hirmondo, B. Muller, J. Konvalinka, P. V.  Coveney, H.-G. Krausslich, V. Muller. (2013). PLoS Comp Biol. Gag-Pol Processing during HIV-1 Virion Maturation: a Systems Biology Approach. 9(6): e1003103