Featured publication: BAlaS – a rapid method for computational alanine scanning

Alanine-scanning mutagenesis has proven to be a key experimental tool to identify the residues that are most important for mediating interactions between a protein and a ligand (which could be a small molecule, a nucleic acid, a different protein, or a different region within the same protein, etc.). However, mutating individual / combinations of amino acids to alanine experimentally is both time-consuming and costly. Consequently, several computational alanine scanning (CAS) programs have been developed that enable users to identify hotspot residues that make the greatest contribution to the interaction of interest in silico.

In two recent papers [1, 2], the Sessions and Woolfson groups at the University of Bristol, in collaboration with the Wilson group at the University of Leeds, introduce BUDE Alanine Scan (BAlaS), a command-line tool to run CAS within the BUDE force field [3, 4]. BAlaS enables high-throughput CAS of both individual X-ray crystal structures plus ensembles of structures obtained from NMR / MD analysis. In Ibarra et al. (2019), the authors introduce the BAlaS software, and benchmark its performance relative to a range of pre-existing CAS software, firstly on the SKEMPI database (a database of 3047 binding free energy changes upon mutation, collated from the literature, for PPIs with known structure), and secondly on newly acquired alanine-scanning mutagenesis data collected for three diverse protein-protein interactions. They find that BAlaS predicts the experimentally identified hotspot residues with comparable accuracy to the best-performing CAS software, whilst running considerably faster. However, the authors also find that averaging the results from all CAS software tested achieves better results than any of the individual programs, and hence recommend CAS users adopt such a meta-scoring approach.

Figure 1: Comparison of experimentally measured vs. computationally predicted (via 6 different CAS software packages) DDG values for individual alanine mutations of interface residues in three diverse protein-protein interactions: a) NOXA-B/MCL-1 (PDB model 1); b) SIMS/SUMO (PDB model 1); and c) GKAP/SHANK-PDZ (chains A and C).

In Wood et al. (2020), the authors introduce an interactive web application to run BAlaS (https://pragmaticproteindesign.bio.ed.ac.uk/balas/). This interface is simple and intuitive, allowing non-expert users to easily run CAS on their own protein-ligand interactions of interest. In addition to allowing mutation of individual residues to alanine, the interface also allows the user to simultaneously mutate constellations of residues (selected either manually or via all permutations of a specified constellation size within a selected subset of residues) to alanine in order to identify “hotspot patches” of residues within the ligand. The capability to perform mutations to residues other than alanine, available in the command-line tool, will be introduced in a future version of the web application.

Figure 2: The BAlaS web interface. Here DDG values are calculated for residues in the transactivation domain of p53 (the “ligand”) bound to MDM2 (the “receptor”) (PDB structure 1YCR).


  1. A. A. Ibarra et al., Predicting and experimentally validating hot-spot residues at protein–protein interfaces. ACS Chem Biol 14, 2252-2263 (2019).
  2. C. W. Wood et al., BAlaS: fast, interactive and accessible computational alanine-scanning using BudeAlaScan. Bioinformatics (2020).
  3. S. McIntosh-Smith, T. Wilson, A. Á. Ibarra, J. Crisp, R. B. Sessions, Benchmarking energy efficiency, power costs and carbon emissions on heterogeneous systems. The Computer Journal 55, 192-205 (2012).
  4. S. McIntosh-Smith, J. Price, R. B. Sessions, A. A. Ibarra, High performance in silico virtual drug screening on many-core processors. The International Journal of High Performance Computing Applications 29, 119-134 (2015).

BcompB seminar January 13th: Dr David Cole (Immunocore)

BcompB seminar, Monday January 13th, 2-3pm, C42 (Biomedical Sciences Building)


The BcompB seminar in January will be given by Dr David Cole from the company Immunocore. David is a former academic & Welcome Trust Career Development Fellow (at the Cardiff University Institute of Infection & Immunity) and now a group leader at Immunocore, a company that develops T cell receptor mimic therapies (‘biologics’) to target cancer as well as other diseases.

The seminar will include results of soon-to-be-published papers where MD simulation and analysis has contributed significantly to the insights obtained.


Title: In silico development of TCR-based therapies



Soluble bispecific T-cell engagers – next generation cancer immunotherapies:

T cell receptor (TCR)-based therapeutics are currently being developed as the next generation of cancer immunotherapies. A major target for these TCR-based therapies are tumour-associated peptide-human leukocyte antigen complexes (pHLA) because they represent the largest pool of cell surface expressed cancer-specific epitopes.


Engineering a TCR for drug development:

In order to generate a soluble TCR-based drug, we affinity enhance our molecules by over 1-million-fold so that stick to the cancer cell for many hours. We then fuse a T cell stimulator to the other end, effectively turning all of the T cells in a patient’s blood into potential cancer killers. The enhanced affinity of the TCR also ensures potency against even the lowest levels of peptide-human leukocyte antigen complexes (pHLA). These drugs (called ImmTACs) are currently being tested in several clinical trials for a range of diseases.


Computational approaches for uncovering biological mechanisms and developing next generation TCR-based drugs:

Here, the use of structural and computational approaches will be discussed as tools to, 1) better understand the TCR-pHLA interactions, 2) uncover the molecular rules that enable TCRs to be engineered with very strong binding affinities, and 3) develop in silico-based rationale design approaches to generate TCRs with improved specificity and potency for the next generation of TCR-based drugs.

Featured Publication: Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking

Intricate molecular choreography separates the bound and unbound states of proteins, resulting in slow binding kinetics that make simulating these events difficult. Interactive molecular dynamics (iMD) allows simulations to be driven to a desired state using a combination of human chemical and spatial intuition and current advances present virtual reality (VR) as a novel strategy for simulation biasing. Previous work shows VR interfaces to iMD (iMD-VR) are sufficiently performant for basic molecular manipulation tasks, but this begs the question of whether these interfaces can be used for more complex tasks, namely correctly establishing bound poses between proteins and ligands.

Our iMD-VR framework for interactively chaperoning drug unbinding and rebinding events was tested on a cohort of non-expert users (n=10), defined as being unfamiliar with the iMD-VR interface. Three example protein-ligand systems were chosen, and participants were asked to undock and redock a ligand from these proteins twice, first with the aid of a trace representation of the ligand in the correct position to guide them, and once again with no trace guide present. Below is a representation of two people in VR undocking a ligand from a protein, and also the three protein-ligand systems used in the study, with key interactions highlighted.

A: Trypsin-Benzamidine, B: Neuraminidase-Oseltamivir, C: HIV-1 Protease-Amprenavir

We show that it is possible to unbind and rebind ligands from three protein targets in a simulation timescale totalling less than 50ps, simulated at a rate of 4.5 ps/min of real time. Where non-expert users had trace atoms showing them the correct pose, all users were able to establish a docking pose within 2Å of the starting structure (1Å for two out of the three tasks). Where no trace atoms were present, binding poses understandably had higher variation, however, participants were still able to get within the same range of RMSD for all three systems. These results were achieved within a single hour-long training session with each participant and are presented below.

Our results show that, even with very limited experience, iMD-VR is performant enough to allow (a) unbinding of a ligand from a protein binding pocket and (b) re-establishment of the original binding pose, demonstrating iMD-VR as a useful tool for sampling states where a ligand is both bound and unbound from a protein.


Helen M. Deeks, Rebecca K. Walters, Stephanie R. Hare, Michael B. O’Connor, Adrian J. Mulholland and David R. Glowacki


doi: to be added very soon!

BcompB meeting July 16th

BcompB meeting on simulations methods for allosteric signal propagation

Tuesday July 16th, 2-3pm, C42

Our next BcompB meeting will take place on July 16th, 2-3pm in C42. We will hear about and discuss simulation methods to look into allosteric communication/signal propagation.

Eric Lang and Sofia Oliveira will be speaking about methods that they have developed and applied.

All welcome!

Eric Lang
Calculated pKa Variations Expose Dynamic Allosteric Communication Networks

Allosteric regulation of protein function, the process by which binding of an effector molecule provokes a functional response from a distal site, is critical for metabolic pathways. Yet, the way the allosteric signal is communicated remains elusive, especially in dynamic, entropically driven regulation mechanisms for which no major conformational changes are observed. To identify these dynamic allosteric communication networks, we have developed an approach that monitors the pKa variations of ionizable residues over the course of molecular dynamics simulations performed in the presence and absence of an allosteric regulator. As the pKa of ionizable residues depends on their environment, it represents a simple metric to monitor changes in several complex factors induced by binding an allosteric effector. These factors include Coulombic interactions, hydrogen bonding, and solvation, as well as backbone motions and side chain fluctuations. The predictions that can be made with this method concerning the roles of ionizable residues for allosteric communication can then be easily tested experimentally by changing the working pH of the protein or performing single point mutations.


Sofia Oliveira

Signal propagation in nicotinic receptors: contributions from equilibrium and nonequilibrium simulations

Nicotinic acetylcholine receptors (nAChRs) modulate synaptic transmission in the nervous system. These receptors have emerged as therapeutic targets in drug discovery for treating several conditions, including Alzheimer’s, pain and nicotine addiction. Despite the impressive progress made in the study of this family of receptors, the conformational changes induced by agonist binding/unbinding and how those are communicated to the ion channel remain poorly defined. This is fundamentally important for understanding biological function as well as crucial for rational drug discovery. Here, we have developed a novel computational strategy combing extensive equilibrium and nonequilibrium molecular dynamics simulations to map dynamic and structural changes induced by nicotine in the human α4β2 nAChR. This approach revealed a striking pattern of communication between the binding pockets and the transmembrane domains and allowed for the identification of the sequence of conformational changes associated with the initial steps in this process.

(See Sophia’s recent paper in Structure)

Featured Publication: Projector-Based Embedding Eliminates Density Functional Dependence for QM/MM Calculations of Reactions in Enzymes and Solution

In this recent publication included in the ‘Women in Computational Chemistry’ special issue of the Journal of Chemical Information and Modeling, we investigate the dependence of predicted reaction energetics on the choice of density functional and QM region size used in QM/MM calculations. DFT methods potentially offer a good combination of accuracy and computational cost but suffer from some well-known limitations and are not systematically improvable. The Claisen rearrangement of chorismate to prephenate, a simple unimolecular reaction catalysed by the enzyme chorismate mutase, was used as a model system to investigate how these choices for QM/MM calculations impact the predicted energetics of reaction.

There are many different density functionals available and the best density functional to choose for any application is not obvious. Commonly used density functionals (e.g. B3LYP, BH&HLYP, MO6-2X) predict barrier heights for the reaction in the enzyme that differ by as much 13 kcal/mol. When different density functionals give different results for the same system, which result should be preferred? Ab initio methods are potentially highly accurate and are systematically improvable but often restricted by their computational cost. Projector-based embedding allows the incorporation of ab initio methods into QM/MM calculations at reasonable computational cost as a small number of atoms can be selected for treatment at the highest levels. Embedding SCS-MP2 in DFT in these QM/MM calculations reduced the spread in predicted barrier height from 13 kcal/mol to 0.3 kcal/mol, essentially eliminating the dependence on the density functional, as shown below (top: standard DFT, bottom: SCS-MP2-in-DFT).


The optimum size of the QM region in QM/MM calculations is a matter of much debate in the literature. The effect of the size of the QM region was tested in solution (by adding additional water molecules to the QM region) and in the enzyme (by adding additional arginine side chains) showing that the difference in barrier heights predicted by common density functionals for any size of the QM region is significantly larger than the change in barrier caused by increasing the size of the QM region.


Ranaghan, K. E.,  Shchepanovska, D., Bennie, S. J.,  Lawan, N., Macrae, S. J., Zurek, J., Manby, F. R. and Mulholland, A. J.
J. Chem. Inf. Model., 2019
DOI: 10.1021/acs.jcim.8b00940

BcompB seminar May 24th: Prof Charles Laughton (Nottingham)

BcompB seminar, Friday May 24th, 2-3pm, C44 (Biomedical Sciences building)

The BcompB seminar in May will be given by Charles (Charlie) Laughton, Professor of Computational Pharmaceutical Science at the University of Nottingham ( https://www.nottingham.ac.uk/pharmacy/people/charles.laughton ).

All welcome!


Enhancing conformational sampling of biomolecules with machine learning and the cloud

Abstract:  I will describe some of our recent research developing new methods for the enhanced sampling of the conformational space of biomolecules, both large and small. I will concentrate on methods that combine molecular dynamics-based sampling with machine learning based supervision in iterative, adaptive, workflows. I will also describe the cloud-based infrastructure and workflow tools we have developed to support this type of research, which we are now making generally available.

BcompB meeting March 19th 2019

BcompB meeting on Molecular Docking

Tuesday March 19th, 2-3pm, C42

During this meeting, we will discuss various aspects molecular docking, including docking small-molecule databases (e.g. to discover lead compounds), protein-protein docking and flexible protein-ligand docking.

With contributions from Richard Sessions, Amaurys Ávila  Ibarra, Debbie Shoemark, Sam Johns and Charlie Colenso, some of the experience in Bristol is highlighted, and indications are given how you can use techniques yourself.

All welcome!


Featured Publication: Unpicking the Cause of Stereoselectivity in Actinorhodin Ketoreductase Variants with Atomistic Simulations

Stefano Artin Serapian and Marc W. van der Kamp

ACS Catalysis
DOI: 10.1021/acscatal.8b04846
Publication Date (Web): January 31, 2019


In this recent ACS Catalysis publication, Stefano Serapian and Marc van der Kamp used a variety of computational tools to shed light on an enticing problem in biocatalysis that has proven very difficult to solve experimentally.

Our enzyme of interest—actinorhodin ketoreductase (actKR)—is found in the soil bacterium Streptomyces coelicolor, where it is normally implicated in the biosynthesis of the antibiotic actinorhodin.  In addition to actKR’s natural scope, as is the case with other ketoreductases, some of its re-engineered variants are highly attractive to synthetic chemists by virtue of their high stereoselectivity in reducing small-molecule achiral ketones to chiral alcohols.

Experimental work on actKR featuring the small model substrate trans-1-decalone (a bicyclic aliphatic ketone) and similarly-sized chiral alcohols suggests that whereas the wild-type enzyme is mildly S-selective, some variants (e.g. the P94L mutant) were entirely S- selective, whereas others (e.g. the V151L mutant) only exhibited R- selectivity.

Featuring classical MD, MM/PBSA and hybrid QM/MM MD with umbrella sampling, our study successfully unravels the causes of such remarkable behaviour in wild-type, P94L, and V151L actKR towards trans-1-decalone.  Explicitly examining both enantiomers of this naturally racemic substrate (something difficult to achieve in vitro), we conclude that changes in stereocontrol across actKR variants can be dictated by a subtle interplay of different causes (including reaction barrier height and accessibility of reactive poses). Interestingly, however, which factor is dominant in conferring stereoselectivity differs per variant.

The protocols we have used were chosen such that they (1) require input of the WT structure only; (2) use relatively limited computational resources (short simulations and semiempirical QM treatment); and (3) can be automated. Our study is thereby a good example of how computational biochemistry can become a practical, useful and efficient tool in biocatalyst engineering, offering perspectives that might otherwise be difficult to explore in vitro.

BcompB seminar Jan 15th: Prof Carmen Domene – Studies of TRP channel activation and modulation using computational approaches

The first BcompB meeting in 2019 will be an external seminar from Prof Carmen Domene (University of Bath).

It will take place on Jan 15th, 2-3pm in LT4 in the School of Chemistry.

Carmen is an expert in the structure, dynamics and mechanism of trans-membrane channels, which her group studies through atomistic molecular dynamics simulations, including enhanced sampling techniques (such as metadynamics).

She will give a talk entitled:

“Studies of TRP channel activation and modulation using computational approaches”


Transient receptor potential (TRP) ion channels constitute a notable family of cation channels involved in the ability of organisms to detect noxious mechanical, thermal and chemical stimuli that gives rise to the perception of pain. One of the most experimentally studied agonist of TRP channels is capsaicin, which is responsible for the burning sensation produced when chili pepper is in contact with organic tissues. Understanding how TRP channels are regulated by capsaicin and other natural products is essential to high impact pharmacological applications, particularly those related to pain treatment. By selected examples from the work we have carried out, I will provide an overview of the current knowledge we have about activation, permeation and selectivity of one of these human molecular thermometers.

Featured publication: Long and large simulation of a megadalton peptide cage – implications for design.

Our manuscript entitled, “The dynamical interplay between a megadalton peptide nanocage and solutes probed by microsecond atomistic MD; implications for design”  has been accepted for publication in Physical Chemistry Chemical Physics (PCCP), (2018), DOI: 10.1039/c8cp06282j. Deborah K. Shoemark, Amaurys Avila Ibarra, James F. Ross, Joseph L. Beesley, Harriet E.V. Bray, Majid Mosayebi, Noah Linden, Tanniemola B. Liverpool, Simon N. McIntosh-Smith, Derek N. Woolfson and Richard B. Sessions.

Here we present the lessons learnt from performing atomistic simulations of 0.6 – 1 microseconds of three ~42 million atom peptide nanocage (SAGE) systems, with and without protein and small molecule solutes. Using GROMACS and the UK supercomputer Archer, data were collected over 2 years. Detailed analysis reveals the structural integrity/helical stability of the SAGEs themselves, how SAGEs interact with the proteins and small molecule species in the systems, whether contact with SAGE influences the native fold of solute proteins and how frequently solutes or ions pass through pores in the SAGEs. Knowing how and where to elaborate and/or modify the SAGE building blocks is important to inform the design process for this synthetic biological approach to diverse applications.  As a vaccine delivery platform, SAGEs that are modular and reproducible, could be tailored to respond to emerging infectious threats more rapidly than conventional methods. For targeted drug delivery, adding peptides that bind SAGEs packed with drug, to specific cell types could reduce dosage demand and side-effects. As nanoreactors for complex chemistry, encapsulating enzyme pathways may allow for more efficient and environmentally friendly catalysis.