Agastya Prakash Bhati

University College London | UCL · Department of Chemistry

Free energy calculations for protein-ligand complexes have become widespread in recent years owing to several conceptual, methodological and technological advances. Central among these is the use of ensemble methods which permits accurate, precise and reproducible predictions and are necessary for uncertainty quantification. Absolute binding free e...

Free energy calculations for protein-ligand complexes have become widespread in recent years owing to several conceptual, methodological and technological advances. Central among these is the use of ensemble methods which permits accurate, precise and reproducible predictions and are necessary for uncertainty quantification. Absolute binding free e...

Active learning (AL) is a specific instance of sequential experimental design and uses machine learning to intelligently choose the next data point or batch of molecular structures to be evaluated. In this sense, it closely mimics the iterative design-make-test-analysis cycle of laboratory experiments to find optimized compounds for a given design...

Free energy calculations for protein-ligand complexes have become widespread in recent years owing to several conceptual, methodological and technological advances. Central among these is the use of ensemble methods which permits accurate, precise and reproducible predictions. Abso- lute binding free energies (ABFEs) are challenging to predict usin...

Active learning (AL) is a specific instance of sequential experimental design and uses machine learning to intelligently choose the next data point or batch of molecular structures to be evaluated. In this sense it closely mimics the iterative design-make-test-analysis cycle of laboratory experiments to find optimized compounds for a given design t...

It is increasingly widely recognized that ensemble-based approaches are required to achieve reliability, accuracy, and precision in molecular dynamics calculations. The purpose of the present article is to address a frequently raised question: what is the optimal way to perform ensemble simulation to calculate quantities of interest?

Alchemical relative binding free energy calculations have recently found important applications in drug optimization. A series of congeneric compounds are generated from a preidentified lead compound, and their relative binding affinities to a protein are assessed in order to optimize candidate drugs. While methods based on equilibrium thermodynami...

We subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets, 3-chymotrypsin-like protease (3CLPro), papain-like protease, and adenosine ribose phosphatase, to long time scale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10 μs simulations for each system, we accurate...

We subject a series of five protein-ligand systems which contain important SARS- CoV-2 targets - 3-chymotrypsin-like protease, papain-like protease and adenosine ribose phosphatase - to long-timescale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10-microsecond simulations for each system, we accurat...

We subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets - 3-chymotrypsin-like protease, papain-like protease and adenosine ribose phosphatase - to long- timescale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10-microsecond simulations for each system, we accurat...

Relative binding free energy (RBFE) calculations are widely used to aid the process of drug discovery. TIES, Thermodynamic Integration with Enhanced Sampling, is a dual-topology approach to RBFE calculations with support for NAMD and OpenMM molecular dynamics engines. The software has been thoroughly validated on publicly available datasets. Here w...

We subject a series of five protein-ligand systems which contain important SARS-CoV-2 targets - 3-chymotrypsin-like protease, papain-like protease and adenosine ribose phosphatase - to long- timescale and adaptive sampling molecular dynamics simulations. By performing ensembles of ten or twelve 10-microsecond simulations for each system, we accurat...

Computational methods and recently modern machine learning methods have played a key role in structure-based drug design. Though several benchmarking datasets are available for machine learning applications in virtual screening, accurate prediction of binding affinity for a protein-ligand complex remains a major challenge. New datasets that allow f...

Despite the increasingly wide availability of computational resources, it is still challenging for researchers to perform comprehensive molecular dynamics (MD) simulations on an industrial scale. With ensemble approaches, great accuracy and precision are achievable at the cost of considerable computational efforts. There is a trade-off between accu...

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration wit...

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat a myriad of diseases. In this work, we examine the computation of...

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcript...

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcripti...

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Rece...

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration wit...

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration wit...

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent...

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcripti...

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat myriad diseases. In this work we examine the computation of alche...

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent...

Although researchers have been working tirelessly since the COVID-19 outbreak, so far only three drugs – remdesivir, ronapreve and molnupiravir – have been approved for use in some countries which directly target the SARS-CoV-2 virus. Given the slow pace and substantial costs of new drug discovery and development, together with the urgency of the m...

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie...

Based on a careful examination of the onset of violet colored dots along the filaments in the developing floral bud stage and the formation of alternating bands of violet and white color in the matured flowers of Passiflora incarnata (Passion flower), it is concluded that the pattern arises from a competition between the production of violet colore...

Although researchers have been working tirelessly since the COVID-19 outbreak, so far only two drugs – remdesivir and ronapreve – have been approved for use in some countries which directly target the SARS-CoV-2 virus. Given the slow pace and substantial costs of new drug discovery and development, together with the urgency of the matter, repurposi...

Although researchers have been working tirelessly since the COVID-19 outbreak, so far only two drugs – remdesivir and ronapreve – have been approved for use in some countries which directly target the SARS-CoV-2 virus. Given the slow pace and substantial costs of new drug discovery and development, together with the urgency of the matter, repurposi...

Although researchers have been working tirelessly since the COVID-19 outbreak, there is yet no effective drug found to directly treat the disease. Given the slow pace and substantial costs of new drug discovery and development, repurposing of existing drugs for the ongoing disease becomes an attractive proposition. In a recent study, a high-through...

Although researchers have been working tirelessly since the COVID-19 outbreak, there is yet no effective drug found to directly treat the disease. Given the slow pace and substantial costs of new drug discovery and development, repurposing of existing drugs for the ongoing disease becomes an attractive proposition. In a recent study, a high-through...

COVID-19 has claimed more than 2.7 × 106 lives and resulted in over 124 × 106 infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. We discuss innovations in computational infrastructure and methods that are accelerating and advancing drug design. Specifically, we describe several methods that integrate artificial intel...

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie...

The TIES (Thermodynamic Integration with Enhanced Sampling) protocol is a formally exact alchemical approach in computational chemistry to the calculation of relative binding free energies. The validity of TIES relies on the correctness of matching atoms across compared pairs of ligands, laying the foundation for the transformation along an alchemi...

A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their com...

COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE recently established the Medical Therapeutics project as part of the National Virtual Biotechnology Laboratory, and tasked it with creating the computational infrastructure...

A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their com...

The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silicomethodologies need to be improved to better select lead compounds that can proceed to later s...

The accurate prediction of the binding affinity changes of drugs caused by protein mutations is a major goal in clinical personalised medicine. We have developed an ensemble-based free energy approach called thermodynamic integration with enhanced sampling (TIES), which yields accurate, precise and reproducible binding affinities. TIES has been sho...

The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug discovery and personalised medicine. The use of in silico methods to predict binding affinities has been largely confined to academic research until recently, primarily due to the lack of their reproducibility, as well as unaffordably longer time to sol...

The alchemical free energy methods have gained much importance recently from several reports of improved ligand-protein binding affinity predictions based on their implementation using molecular dynamics simulation. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are avail...

Optimisation of ligand binding affinity to the target protein of interest is a primary objective in small-molecule drug discovery. Until now, the prediction of binding affinities by computational methods has not been widely applied in the drug discovery process, mainly due to its lack of accuracy and reproducibility, as well as the long turnaround...

An understanding of the determinants of the thermal stability of thermostable proteins is expected to enable design of enzymes that can be employed in industrial biocatalytic processes carried out at high temperatures. A major factor that has been proposed to stabilize thermostable proteins is the high occurrence of salt bridges. The current study...

Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical funct...

The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug discovery and personalised medicine. The time taken to make such predictions is of similar importance to their accuracy, precision and reliability. In the last few years, an ensemble based molecular dynamics approach has been proposed that provides a ro...

We present FabSim, a toolkit developed to simplify a range of computational tasks for researchers in diverse disciplines. FabSim is flexible, adaptable, and allows users to perform a wide range of tasks with ease. It also provides a systematic way to automate the use of resourcess, including HPC and distributed resources, and to make tasks easier t...