Bruno E. Correia

De novo design of light-controlled conformational protein switches

This paper computationally designs light-responsive proteins that undergo conformational changes upon light activation, enabling precise control of biological functions.

Computational design of protein conformational landscapes for metamorphic behavior

This study designs metamorphic proteins that switch between multiple conformations and shows how mutations can shift their conformational equilibrium.

A Unified 3D Generative Model for Synthesizable Structure-Based Drug Design

This paper introduces LDDM, a generative model for drug design that produces synthetically accessible compounds validated experimentally for five protein targets.

Mapping the latent CRBN-molecular glue degrader interactome

The paper identifies CRBN-pomalidomide binders using a combination of GluePCA and AI-derived protein surface queries, revealing known and novel interactors for MGD development.

The Human Bindome: A Proteome-scale Atlas of Designed Binder Candidates

A parallelized BindCraft pipeline generated 306,146 in silico binder candidates against 8,296 human proteins, each with sequence, predicted complex and confidence metrics, freely accessible online.

A generalizable interface-seeded framework for de novo design of functional oligomers

This paper introduces an AI-based framework for designing responsive protein oligomers that assemble in response to chemical or phosphorylation triggers, validated through experimental testing.

Computational design of microbial and animal rhodopsin soluble analogues

This study computationally designs soluble analogues of animal and microbial rhodopsins, showing they are well-folded, thermostable, and retain retinal photocycle functionality.

Induced Estrogen Receptor SUMOylation drives SERD activity

This study shows that SERDs induce ER SUMOylation, which recruits co-repressors to suppress transcription, rather than relying on ER degradation for their activity.

De novo Design of Polymorph-Specific Binders Targeting α-Synuclein Fibrils

This study designs polymorph-specific binders for α-synuclein fibrils using a computational pipeline, demonstrating their utility as selective labeling agents without interfering with fibril dynamics.

Deep learning-enabled scaffolding of spatial arrays of PfCSP epitopes

This study uses deep learning to design multi-epitope scaffolds mimicking CSP's spatial structure, showing accurate positioning of two epitopes and partial success with the third.

Decoding epitope immunodominance in HIV Env using cryoEM and machine learning

This study uses cryoEM and machine learning to predict and redirect immunodominant epitopes in HIV Env, showing improved vaccine antigen design.

Drug-controlled CAR-T cells through the regulation of cell-cell interactions

This paper develops DROP-CARs, drug-regulated CAR-T cells that control cell-cell interactions using small-molecule switches, showing in vitro and in vivo functionality.

Molecular basis for anti-jumbo phage immunity by AVAST Type 5

This study identifies Avs5 systems as a conserved bacterial defense against jumbo phages, revealing their mechanism of recognizing and disrupting phage infection.

Mapping targetable sites on the human surfaceome for the design of novel binders

The paper identifies 4,500 targetable sites on the human surfaceome and introduces binder seeds for protein design, validated through experimental approaches and supported by a database.

FragmentScope - exploring the fragment space with learned surface representations

FragmentScope uses learned protein surface representations to guide fragment placement and small molecule design, achieving accurate placement and promising lead compounds.

Accurate single domain scaffolding of three non-overlapping protein epitopes using deep learning

This paper designs small single domain proteins that present three distinct viral epitopes using deep learning, showing improved immunogenicity compared to single-epitope designs.

Leveraging protein representations to explore uncharted fold spaces with generative models

This paper introduces DiffTopo, a diffusion model for generating novel protein folds, and MirrorTopo, a pipeline to expand known fold space by mirroring native protein topologies.

Rational design of chemically responsive cytokines for cancer immunotherapy

This paper designs switchable cytokines that are activated by Venetoclax, showing tumor control comparable to native cytokines and enhancing therapeutic safety.

De novo design of phosphorylation-induced protein switches for synthetic signaling in cells

This paper designs phosphorylation-induced protein switches that control transcription in cells, demonstrating their functionality in synthetic signaling.

Humanized Caffeine-Inducible Systems for Controlling Cellular Functions

The paper develops caffeine-inducible systems for controlling gene expression in human cells using humanized protein components and demonstrates their use in inducible gene expression in T-cells.

Mapping the Structural Landscape of Amyloid Fibrils to Guide Polymorph-Specific Therapeutics

This paper introduces FibrilSite, a computational pipeline to identify structural features of amyloid fibrils, revealing conserved and polymorph-specific sites that guide drug discovery.

Crowdsourced Protein Design: Lessons From the Adaptyv EGFR Binder Competition

The paper analyzes a crowdsourced protein design competition, showing participants designed EGFR binders with varying affinities and highlighting challenges in benchmarking and experimental design.

BoltzDesign1: Inverting All-Atom Structure Prediction Model for Generalized Biomolecular Binder Design

BoltzDesign1 inverts AlphaFold3 to design protein binders for diverse targets without model finetuning, achieving high in silico success rates and structural diversity.

Boosting protein graph representations through static-dynamic fusion

The paper introduces a graph representation that combines static and dynamic protein data, improving performance in three tasks related to protein-ligand interactions.

Computationally designed stem-epitope mimetics elicit broadly reactive antibodies

This study designs stem-epitope mimetics using computational methods to elicit broadly reactive antibodies against influenza viruses.

Targeting protein-ligand neosurfaces using a generalizable deep learning approach

This paper designs proteins that target neosurfaces from protein-ligand complexes using a deep learning approach, validated experimentally against three drug-bound protein complexes.

Structure-based Design of Chimeric Influenza Hemagglutinins to Elicit Cross-group Immunity

This paper designs chimeric influenza hemagglutinins that combine antigenic surfaces from different strains to elicit cross-group immunity and neutralize multiple strains.

A modular toolbox for the optogenetic deactivation of transcription

The paper introduces LOOMINA, an optogenetic system that deactivates transcriptional activation in response to blue light, offering high adaptability and compatibility with various effector proteins.

A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins

The paper develops a deep mutational scanning pipeline for anti-CRISPR proteins in E. coli, revealing their mutational tolerance and redundancy, and validates findings in mammalian cells.

Structures of the Foamy virus fusion protein reveal an unexpected link with the F protein of paramyxo- and pneumoviruses

The paper reports cryo-EM structures of foamy virus Env in pre- and post-fusion states, revealing structural similarity to paramyxovirus F proteins and suggesting an evolutionary link.